{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dUeKVCYTbcyT"
   },
   "source": [
    "#### Copyright 2019 The TensorFlow Authors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:04.896788Z",
     "iopub.status.busy": "2023-11-08T01:16:04.896220Z",
     "iopub.status.idle": "2023-11-08T01:16:04.900649Z",
     "shell.execute_reply": "2023-11-08T01:16:04.899945Z"
    },
    "id": "4ellrPx7tdxq"
   },
   "outputs": [],
   "source": [
    "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "# https://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7JfLUlawto_D"
   },
   "source": [
    "# 不平衡数据的分类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DwdpaTKJOoPu"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td><a target=\"_blank\" href=\"https://tensorflow.google.cn/tutorials/structured_data/imbalanced_data\" class=\"\"><img src=\"https://tensorflow.google.cn/images/tf_logo_32px.png\" class=\"\">在 TensorFlow.org 上查看</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs-l10n/blob/master/site/zh-cn/tutorials/structured_data/imbalanced_data.ipynb\" class=\"\"><img src=\"https://tensorflow.google.cn/images/colab_logo_32px.png\" class=\"\">在 Google Colab 中运行</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/docs-l10n/blob/master/site/zh-cn/tutorials/structured_data/imbalanced_data.ipynb\" class=\"\"><img src=\"https://tensorflow.google.cn/images/GitHub-Mark-32px.png\" class=\"\">在 GitHub 上查看源代码</a></td>\n",
    "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/docs-l10n/site/zh-cn/tutorials/structured_data/imbalanced_data.ipynb\" class=\"\"><img src=\"https://tensorflow.google.cn/images/download_logo_32px.png\" class=\"\">下载笔记本</a></td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mthoSGBAOoX-"
   },
   "source": [
    "本教程演示了如何对高度不平衡的数据集进行分类，在此类数据集中，一类中的样本数量远多于另一类中的样本数量。您将使用 Kaggle 上托管的 [Credit Card Fraud Detection](https://www.kaggle.com/mlg-ulb/creditcardfraud) 数据集，目的是从总共 284,807 笔交易中检测出仅有的 492 笔欺诈交易。您将使用 [Keras](../../guide/keras/overview.ipynb) 来定义模型和[类权重](https://tensorflow.google.cn/versions/r2.0/api_docs/python/tf/keras/Model)，从而帮助模型从不平衡数据中学习。\n",
    "\n",
    "本教程包含下列操作的完整代码：\n",
    "\n",
    "- 使用 Pandas 加载 CSV 文件。\n",
    "- 创建训练、验证和测试集。\n",
    "- 使用 Keras 定义并训练模型（包括设置类权重）。\n",
    "- 使用各种指标（包括精确率和召回率）评估模型。\n",
    "- 尝试使用常见技术来处理不平衡数据，例如：\n",
    "    - 类加权\n",
    "    - 过采样\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kRHmSyHxEIhN"
   },
   "source": [
    "## 设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:04.904826Z",
     "iopub.status.busy": "2023-11-08T01:16:04.904116Z",
     "iopub.status.idle": "2023-11-08T01:16:08.308434Z",
     "shell.execute_reply": "2023-11-08T01:16:08.307251Z"
    },
    "id": "JM7hDSNClfoK"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-08 01:16:05.391090: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
      "2023-11-08 01:16:05.391146: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
      "2023-11-08 01:16:05.392950: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "\n",
    "import os\n",
    "import tempfile\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "import sklearn\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:08.313415Z",
     "iopub.status.busy": "2023-11-08T01:16:08.312672Z",
     "iopub.status.idle": "2023-11-08T01:16:08.317453Z",
     "shell.execute_reply": "2023-11-08T01:16:08.316671Z"
    },
    "id": "c8o1FHzD-_y_"
   },
   "outputs": [],
   "source": [
    "mpl.rcParams['figure.figsize'] = (12, 10)\n",
    "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z3iZVjziKHmX"
   },
   "source": [
    "## 数据处理与浏览"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4sA9WOcmzH2D"
   },
   "source": [
    "### 下载 Kaggle Credit Card Fraud 数据集\n",
    "\n",
    "Pandas 是一个 Python 库，其中包含许多有用的实用工具，用于加载和使用结构化数据，并可用于将 CSV 下载到数据帧中。\n",
    "\n",
    "注：Worldline 和 ULB（布鲁塞尔自由大学）[机器学习小组](http://mlg.ulb.ac.be)在大数据挖掘和欺诈检测的合作研究期间，已对此数据集进行了收集和分析。与相关主题当前和过去项目有关的详细信息，请访问[这里](https://www.researchgate.net/project/Fraud-detection-5)和 [DefeatFraud](https://mlg.ulb.ac.be/wordpress/portfolio_page/defeatfraud-assessment-and-validation-of-deep-feature-engineering-and-learning-solutions-for-fraud-detection/) 项目页面。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:08.320854Z",
     "iopub.status.busy": "2023-11-08T01:16:08.320603Z",
     "iopub.status.idle": "2023-11-08T01:16:12.040100Z",
     "shell.execute_reply": "2023-11-08T01:16:12.039415Z"
    },
    "id": "pR_SnbMArXr7"
   },
   "outputs": [
    {
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       "      <td>0.133558</td>\n",
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       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
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       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
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       "      <td>-0.255425</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>2.69</td>\n",
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       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "      <td>378.66</td>\n",
       "      <td>0</td>\n",
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       "      <th>3</th>\n",
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       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "      <td>123.50</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
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       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
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       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
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       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
       "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
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       "3  0.377436 -1.387024  ... -0.108300  0.005274 -0.190321 -1.175575  0.647376   \n",
       "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
       "\n",
       "        V26       V27       V28  Amount  Class  \n",
       "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4  0.502292  0.219422  0.215153   69.99      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = tf.keras.utils\n",
    "raw_df = pd.read_csv('https://storage.googleapis.com/download.tensorflow.org/data/creditcard.csv')\n",
    "raw_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.044353Z",
     "iopub.status.busy": "2023-11-08T01:16:12.043629Z",
     "iopub.status.idle": "2023-11-08T01:16:12.198467Z",
     "shell.execute_reply": "2023-11-08T01:16:12.197674Z"
    },
    "id": "-fgdQgmwUFuj"
   },
   "outputs": [
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       "      <td>1.516255e+00</td>\n",
       "      <td>1.415869e+00</td>\n",
       "      <td>1.380247e+00</td>\n",
       "      <td>4.822270e-01</td>\n",
       "      <td>4.036325e-01</td>\n",
       "      <td>3.300833e-01</td>\n",
       "      <td>250.120109</td>\n",
       "      <td>0.041527</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-5.640751e+01</td>\n",
       "      <td>-7.271573e+01</td>\n",
       "      <td>-4.832559e+01</td>\n",
       "      <td>-5.683171e+00</td>\n",
       "      <td>-1.137433e+02</td>\n",
       "      <td>-2.604551e+00</td>\n",
       "      <td>-2.256568e+01</td>\n",
       "      <td>-1.543008e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>54201.500000</td>\n",
       "      <td>-9.203734e-01</td>\n",
       "      <td>-5.985499e-01</td>\n",
       "      <td>-8.903648e-01</td>\n",
       "      <td>-8.486401e-01</td>\n",
       "      <td>-6.915971e-01</td>\n",
       "      <td>-3.269839e-01</td>\n",
       "      <td>-7.083953e-02</td>\n",
       "      <td>-5.295979e-02</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84692.000000</td>\n",
       "      <td>1.810880e-02</td>\n",
       "      <td>6.548556e-02</td>\n",
       "      <td>1.798463e-01</td>\n",
       "      <td>-1.984653e-02</td>\n",
       "      <td>-5.433583e-02</td>\n",
       "      <td>-5.213911e-02</td>\n",
       "      <td>1.342146e-03</td>\n",
       "      <td>1.124383e-02</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>139320.500000</td>\n",
       "      <td>1.315642e+00</td>\n",
       "      <td>8.037239e-01</td>\n",
       "      <td>1.027196e+00</td>\n",
       "      <td>7.433413e-01</td>\n",
       "      <td>6.119264e-01</td>\n",
       "      <td>2.409522e-01</td>\n",
       "      <td>9.104512e-02</td>\n",
       "      <td>7.827995e-02</td>\n",
       "      <td>77.165000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>172792.000000</td>\n",
       "      <td>2.454930e+00</td>\n",
       "      <td>2.205773e+01</td>\n",
       "      <td>9.382558e+00</td>\n",
       "      <td>1.687534e+01</td>\n",
       "      <td>3.480167e+01</td>\n",
       "      <td>3.517346e+00</td>\n",
       "      <td>3.161220e+01</td>\n",
       "      <td>3.384781e+01</td>\n",
       "      <td>25691.160000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Time            V1            V2            V3            V4  \\\n",
       "count  284807.000000  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean    94813.859575  1.168375e-15  3.416908e-16 -1.379537e-15  2.074095e-15   \n",
       "std     47488.145955  1.958696e+00  1.651309e+00  1.516255e+00  1.415869e+00   \n",
       "min         0.000000 -5.640751e+01 -7.271573e+01 -4.832559e+01 -5.683171e+00   \n",
       "25%     54201.500000 -9.203734e-01 -5.985499e-01 -8.903648e-01 -8.486401e-01   \n",
       "50%     84692.000000  1.810880e-02  6.548556e-02  1.798463e-01 -1.984653e-02   \n",
       "75%    139320.500000  1.315642e+00  8.037239e-01  1.027196e+00  7.433413e-01   \n",
       "max    172792.000000  2.454930e+00  2.205773e+01  9.382558e+00  1.687534e+01   \n",
       "\n",
       "                 V5           V26           V27           V28         Amount  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  284807.000000   \n",
       "mean   9.604066e-16  1.683437e-15 -3.660091e-16 -1.227390e-16      88.349619   \n",
       "std    1.380247e+00  4.822270e-01  4.036325e-01  3.300833e-01     250.120109   \n",
       "min   -1.137433e+02 -2.604551e+00 -2.256568e+01 -1.543008e+01       0.000000   \n",
       "25%   -6.915971e-01 -3.269839e-01 -7.083953e-02 -5.295979e-02       5.600000   \n",
       "50%   -5.433583e-02 -5.213911e-02  1.342146e-03  1.124383e-02      22.000000   \n",
       "75%    6.119264e-01  2.409522e-01  9.104512e-02  7.827995e-02      77.165000   \n",
       "max    3.480167e+01  3.517346e+00  3.161220e+01  3.384781e+01   25691.160000   \n",
       "\n",
       "               Class  \n",
       "count  284807.000000  \n",
       "mean        0.001727  \n",
       "std         0.041527  \n",
       "min         0.000000  \n",
       "25%         0.000000  \n",
       "50%         0.000000  \n",
       "75%         0.000000  \n",
       "max         1.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df[['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V26', 'V27', 'V28', 'Amount', 'Class']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xWKB_CVZFLpB"
   },
   "source": [
    "### 检查类标签的不平衡\n",
    "\n",
    "让我们看一下数据集的不平衡情况："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.202864Z",
     "iopub.status.busy": "2023-11-08T01:16:12.202069Z",
     "iopub.status.idle": "2023-11-08T01:16:12.207941Z",
     "shell.execute_reply": "2023-11-08T01:16:12.207228Z"
    },
    "id": "HCJFrtuY2iLF"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Examples:\n",
      "    Total: 284807\n",
      "    Positive: 492 (0.17% of total)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "neg, pos = np.bincount(raw_df['Class'])\n",
    "total = neg + pos\n",
    "print('Examples:\\n    Total: {}\\n    Positive: {} ({:.2f}% of total)\\n'.format(\n",
    "    total, pos, 100 * pos / total))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KnLKFQDsCBUg"
   },
   "source": [
    "这表明正样本的比例很小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6qox6ryyzwdr"
   },
   "source": [
    "### 清理、拆分和归一化数据\n",
    "\n",
    "原始数据有一些问题。首先，`Time` 和 `Amount` 列变化太大，无法直接使用。删除 `Time` 列（因为不清楚其含义），并获取 `Amount` 列的日志以缩小其范围。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.211424Z",
     "iopub.status.busy": "2023-11-08T01:16:12.211127Z",
     "iopub.status.idle": "2023-11-08T01:16:12.238691Z",
     "shell.execute_reply": "2023-11-08T01:16:12.238005Z"
    },
    "id": "Ef42jTuxEjnj"
   },
   "outputs": [],
   "source": [
    "cleaned_df = raw_df.copy()\n",
    "\n",
    "# You don't want the `Time` column.\n",
    "cleaned_df.pop('Time')\n",
    "\n",
    "# The `Amount` column covers a huge range. Convert to log-space.\n",
    "eps = 0.001 # 0 => 0.1¢\n",
    "cleaned_df['Log Amount'] = np.log(cleaned_df.pop('Amount')+eps)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uSNgdQFFFQ6u"
   },
   "source": [
    "将数据集拆分为训练、验证和测试集。验证集在模型拟合期间使用，用于评估损失和任何指标，判断模型与数据的拟合程度。测试集在训练阶段完全不使用，仅在最后用于评估模型泛化到新数据的能力。这对于不平衡的数据集尤为重要，因为[过拟合](https://developers.google.com/machine-learning/crash-course/generalization/peril-of-overfitting)是缺乏训练数据造成的一个重大问题。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.243200Z",
     "iopub.status.busy": "2023-11-08T01:16:12.242470Z",
     "iopub.status.idle": "2023-11-08T01:16:12.465381Z",
     "shell.execute_reply": "2023-11-08T01:16:12.464399Z"
    },
    "id": "xfxhKg7Yr1-b"
   },
   "outputs": [],
   "source": [
    "# Use a utility from sklearn to split and shuffle your dataset.\n",
    "train_df, test_df = train_test_split(cleaned_df, test_size=0.2)\n",
    "train_df, val_df = train_test_split(train_df, test_size=0.2)\n",
    "\n",
    "# Form np arrays of labels and features.\n",
    "train_labels = np.array(train_df.pop('Class'))\n",
    "bool_train_labels = train_labels != 0\n",
    "val_labels = np.array(val_df.pop('Class'))\n",
    "test_labels = np.array(test_df.pop('Class'))\n",
    "\n",
    "train_features = np.array(train_df)\n",
    "val_features = np.array(val_df)\n",
    "test_features = np.array(test_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8a_Z_kBmr7Oh"
   },
   "source": [
    "使用 sklearn StandardScaler 将输入特征归一化。这会将平均值设置为 0，标准偏差设置为 1。\n",
    "\n",
    "注：`StandardScaler` 只能使用 `train_features` 进行拟合，以确保模型不会窥视验证集或测试集。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.469612Z",
     "iopub.status.busy": "2023-11-08T01:16:12.469311Z",
     "iopub.status.idle": "2023-11-08T01:16:12.603866Z",
     "shell.execute_reply": "2023-11-08T01:16:12.603034Z"
    },
    "id": "IO-qEUmJ5JQg"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training labels shape: (182276,)\n",
      "Validation labels shape: (45569,)\n",
      "Test labels shape: (56962,)\n",
      "Training features shape: (182276, 29)\n",
      "Validation features shape: (45569, 29)\n",
      "Test features shape: (56962, 29)\n"
     ]
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "train_features = scaler.fit_transform(train_features)\n",
    "\n",
    "val_features = scaler.transform(val_features)\n",
    "test_features = scaler.transform(test_features)\n",
    "\n",
    "train_features = np.clip(train_features, -5, 5)\n",
    "val_features = np.clip(val_features, -5, 5)\n",
    "test_features = np.clip(test_features, -5, 5)\n",
    "\n",
    "\n",
    "print('Training labels shape:', train_labels.shape)\n",
    "print('Validation labels shape:', val_labels.shape)\n",
    "print('Test labels shape:', test_labels.shape)\n",
    "\n",
    "print('Training features shape:', train_features.shape)\n",
    "print('Validation features shape:', val_features.shape)\n",
    "print('Test features shape:', test_features.shape)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XF2nNfWKJ33w"
   },
   "source": [
    "小心：如果要部署模型，保留预处理计算至关重要。这是将它们实现为层并在导出之前将它们附加到模型最简单的方法。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uQ7m9nqDC3W6"
   },
   "source": [
    "### 查看数据分布\n",
    "\n",
    "接下来通过一些特征比较一下正样本和负样本的分布。此时，建议您问自己如下问题：\n",
    "\n",
    "- 这些分布是否有意义？\n",
    "    - 是。您已对输入进行了归一化处理，而它们大多集中在 `+/- 2` 范围内。\n",
    "- 您是否能看出分布之间的差异？\n",
    "    - 是。正样本包含极值的比率高得多 。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:12.608485Z",
     "iopub.status.busy": "2023-11-08T01:16:12.607638Z",
     "iopub.status.idle": "2023-11-08T01:16:14.737119Z",
     "shell.execute_reply": "2023-11-08T01:16:14.736265Z"
    },
    "id": "raK7hyjd_vf6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos_df = pd.DataFrame(train_features[ bool_train_labels], columns=train_df.columns)\n",
    "neg_df = pd.DataFrame(train_features[~bool_train_labels], columns=train_df.columns)\n",
    "\n",
    "sns.jointplot(x=pos_df['V5'], y=pos_df['V6'],\n",
    "              kind='hex', xlim=(-5,5), ylim=(-5,5))\n",
    "plt.suptitle(\"Positive distribution\")\n",
    "\n",
    "sns.jointplot(x=neg_df['V5'], y=neg_df['V6'],\n",
    "              kind='hex', xlim=(-5,5), ylim=(-5,5))\n",
    "_ = plt.suptitle(\"Negative distribution\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qFK1u4JX16D8"
   },
   "source": [
    "## 定义模型和指标\n",
    "\n",
    "定义一个函数，该函数会创建一个简单的神经网络，其中包含一个密集连接的隐藏层、一个用于减少过拟合的[随机失活](https://developers.google.com/machine-learning/glossary/#dropout_regularization)层，以及一个返回欺诈交易概率的输出 Sigmoid 层： "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:14.741386Z",
     "iopub.status.busy": "2023-11-08T01:16:14.741080Z",
     "iopub.status.idle": "2023-11-08T01:16:17.136142Z",
     "shell.execute_reply": "2023-11-08T01:16:17.135243Z"
    },
    "id": "3JQDzUqT3UYG"
   },
   "outputs": [],
   "source": [
    "METRICS = [\n",
    "      keras.metrics.TruePositives(name='tp'),\n",
    "      keras.metrics.FalsePositives(name='fp'),\n",
    "      keras.metrics.TrueNegatives(name='tn'),\n",
    "      keras.metrics.FalseNegatives(name='fn'), \n",
    "      keras.metrics.BinaryAccuracy(name='accuracy'),\n",
    "      keras.metrics.Precision(name='precision'),\n",
    "      keras.metrics.Recall(name='recall'),\n",
    "      keras.metrics.AUC(name='auc'),\n",
    "      keras.metrics.AUC(name='prc', curve='PR'), # precision-recall curve\n",
    "]\n",
    "\n",
    "def make_model(metrics=METRICS, output_bias=None):\n",
    "  if output_bias is not None:\n",
    "    output_bias = tf.keras.initializers.Constant(output_bias)\n",
    "  model = keras.Sequential([\n",
    "      keras.layers.Dense(\n",
    "          16, activation='relu',\n",
    "          input_shape=(train_features.shape[-1],)),\n",
    "      keras.layers.Dropout(0.5),\n",
    "      keras.layers.Dense(1, activation='sigmoid',\n",
    "                         bias_initializer=output_bias),\n",
    "  ])\n",
    "\n",
    "  model.compile(\n",
    "      optimizer=keras.optimizers.Adam(learning_rate=1e-3),\n",
    "      loss=keras.losses.BinaryCrossentropy(),\n",
    "      metrics=metrics)\n",
    "\n",
    "  return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SU0GX6E6mieP"
   },
   "source": [
    "### 了解有用的指标\n",
    "\n",
    "请注意，上面定义的一些指标可以由模型计算得出，这对评估性能很有帮助。\n",
    "\n",
    "- **假**负例和**假**正例是被**错误**分类的样本\n",
    "- **真**负例和**真**正例是被**正确**分类的样本\n",
    "- **准确率**是被正确分类的样本的百分比\n",
    "\n",
    "> $\\frac{\\text{true samples}}{\\text{total samples}}$\n",
    "\n",
    "- **精确率**是被正确分类的**预测**正例的百分比\n",
    "\n",
    "> $\\frac{\\text{true positives}}{\\text{true positives + false positives}}$\n",
    "\n",
    "- **召回率**是被正确分类的**实际**正例的百分比\n",
    "\n",
    "> $\\frac{\\text{true positives}}{\\text{true positives + false negatives}}$\n",
    "\n",
    "- **AUC** 是指接收器操作特征曲线中的曲线下方面积 (ROC-AUC)。此指标等于分类器对随机正样本的排序高于随机负样本的概率。\n",
    "- **AUPRC** 是指精确率-召回率曲线下方面积。该指标计算不同概率阈值的精度率-召回率对。\n",
    "\n",
    "注：准确率在此任务中不是一个有用的指标。只要始终预测“False”，您就可以在此任务中达到 99.8%+ 的准确率。\n",
    "\n",
    "延伸阅读：\n",
    "\n",
    "- [真与假以及正类别与负类别](https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative)\n",
    "- [准确率](https://developers.google.com/machine-learning/crash-course/classification/accuracy)\n",
    "- [精确率和召回率](https://developers.google.com/machine-learning/crash-course/classification/precision-and-recall)\n",
    "- [ROC-AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc)\n",
    "- [精确率-召回率曲线和 ROC 曲线之间的关系](https://www.biostat.wisc.edu/~page/rocpr.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FYdhSAoaF_TK"
   },
   "source": [
    "## 基线模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IDbltVPg2m2q"
   },
   "source": [
    "### 构建模型\n",
    "\n",
    "现在，使用先前定义的函数创建并训练模型。请注意，该模型使用大于默认的批次大小 (2048) 来进行拟合，这一点很重要，有助于确保每个批次都有一定机会包含少量正样本。如果批次过小，它们可能会没有可供学习的欺诈交易。\n",
    "\n",
    "注：此模型无法很好地处理类不平衡问题。我们将在本教程的后面部分对此进行改进。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:17.140711Z",
     "iopub.status.busy": "2023-11-08T01:16:17.140408Z",
     "iopub.status.idle": "2023-11-08T01:16:17.144720Z",
     "shell.execute_reply": "2023-11-08T01:16:17.143966Z"
    },
    "id": "ouUkwPcGQsy3"
   },
   "outputs": [],
   "source": [
    "EPOCHS = 100\n",
    "BATCH_SIZE = 2048\n",
    "\n",
    "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
    "    monitor='val_auc', \n",
    "    verbose=1,\n",
    "    patience=10,\n",
    "    mode='max',\n",
    "    restore_best_weights=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:17.148453Z",
     "iopub.status.busy": "2023-11-08T01:16:17.147858Z",
     "iopub.status.idle": "2023-11-08T01:16:17.231128Z",
     "shell.execute_reply": "2023-11-08T01:16:17.230354Z"
    },
    "id": "1xlR_dekzw7C"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Layer (type)                Output Shape              Param #   \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=================================================================\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " dense (Dense)               (None, 16)                480       \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " dropout (Dropout)           (None, 16)                0         \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " dense_1 (Dense)             (None, 1)                 17        \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=================================================================\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total params: 497 (1.94 KB)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trainable params: 497 (1.94 KB)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Non-trainable params: 0 (0.00 Byte)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = make_model()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Wx7ND3_SqckO"
   },
   "source": [
    "试运行模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:17.238903Z",
     "iopub.status.busy": "2023-11-08T01:16:17.238585Z",
     "iopub.status.idle": "2023-11-08T01:16:17.680712Z",
     "shell.execute_reply": "2023-11-08T01:16:17.679892Z"
    },
    "id": "LopSd-yQqO3a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "1/1 [==============================] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1/1 [==============================] - 0s 377ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0.12993479],\n",
       "       [0.0831413 ],\n",
       "       [0.24497728],\n",
       "       [0.3017688 ],\n",
       "       [0.33697775],\n",
       "       [0.0949156 ],\n",
       "       [0.1872398 ],\n",
       "       [0.27218476],\n",
       "       [0.29461417],\n",
       "       [0.6366021 ]], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(train_features[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YKIgWqHms_03"
   },
   "source": [
    "### 可选：设置正确的初始偏差。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qk_3Ry6EoYDq"
   },
   "source": [
    "模型最初的猜测不太理想。您知道数据集不平衡，因此需要设置输出层的偏差以反映这种不平衡（请参阅：[训练神经网络的秘诀：“好好初始化”](http://karpathy.github.io/2019/04/25/recipe/#2-set-up-the-end-to-end-trainingevaluation-skeleton--get-dumb-baselines)）。这样做有助于初始收敛。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PdbfWDuVpo6k"
   },
   "source": [
    "使用默认偏差初始化时，损失应约为 `math.log(2) = 0.69314`。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:17.685112Z",
     "iopub.status.busy": "2023-11-08T01:16:17.684458Z",
     "iopub.status.idle": "2023-11-08T01:16:21.002346Z",
     "shell.execute_reply": "2023-11-08T01:16:21.001532Z"
    },
    "id": "H-oPqh3SoGXk"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss: 0.3724\n"
     ]
    }
   ],
   "source": [
    "results = model.evaluate(train_features, train_labels, batch_size=BATCH_SIZE, verbose=0)\n",
    "print(\"Loss: {:0.4f}\".format(results[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hE-JRzfKqfhB"
   },
   "source": [
    "可以用以下代码推导出要设置的正确偏差：\n",
    "\n",
    "$$ p_0 = pos/(pos + neg) = 1/(1+e^{-b_0}) $$ $$ b_0 = -log_e(1/p_0 - 1) $$ $$ b_0 = log_e(pos/neg)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:21.006856Z",
     "iopub.status.busy": "2023-11-08T01:16:21.006165Z",
     "iopub.status.idle": "2023-11-08T01:16:21.011802Z",
     "shell.execute_reply": "2023-11-08T01:16:21.011054Z"
    },
    "id": "F5KWPSjjstUS"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-6.35935934])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_bias = np.log([pos/neg])\n",
    "initial_bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d1juXI9yY1KD"
   },
   "source": [
    "将其设置为初始偏差，模型将给出合理得多的初始猜测。\n",
    "\n",
    "结果应该接近：`pos/total = 0.0018`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:21.015552Z",
     "iopub.status.busy": "2023-11-08T01:16:21.015258Z",
     "iopub.status.idle": "2023-11-08T01:16:21.186636Z",
     "shell.execute_reply": "2023-11-08T01:16:21.185672Z"
    },
    "id": "50oyu1uss0i-"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "1/1 [==============================] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1/1 [==============================] - 0s 81ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0.00022771],\n",
       "       [0.00144273],\n",
       "       [0.00385517],\n",
       "       [0.00052363],\n",
       "       [0.00052137],\n",
       "       [0.00077223],\n",
       "       [0.00100834],\n",
       "       [0.00055533],\n",
       "       [0.00064206],\n",
       "       [0.00016787]], dtype=float32)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = make_model(output_bias = initial_bias)\n",
    "model.predict(train_features[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4xqFYb2KqRHQ"
   },
   "source": [
    "使用此初始化，初始损失应约为：\n",
    "\n",
    "$$-p_0log(p_0)-(1-p_0)log(1-p_0) = 0.01317$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:21.190330Z",
     "iopub.status.busy": "2023-11-08T01:16:21.190044Z",
     "iopub.status.idle": "2023-11-08T01:16:22.088287Z",
     "shell.execute_reply": "2023-11-08T01:16:22.087507Z"
    },
    "id": "xVDqCWXDqHSc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss: 0.0174\n"
     ]
    }
   ],
   "source": [
    "results = model.evaluate(train_features, train_labels, batch_size=BATCH_SIZE, verbose=0)\n",
    "print(\"Loss: {:0.4f}\".format(results[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FrDC8hvNr9yw"
   },
   "source": [
    "此初始损失大约是使用朴素初始化时损失的 50 倍。\n",
    "\n",
    "这样，模型就不需要花费前几个周期去仅仅了解不可能有正样本。这也使得在训练过程中更容易读取损失图。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0EJj9ixKVBMT"
   },
   "source": [
    "### 为初始权重设置检查点\n",
    "\n",
    "为了使各种训练运行更具可比性，请将这个初始模型的权重保存在检查点文件中，并在训练前将它们加载到每个模型中："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:22.092496Z",
     "iopub.status.busy": "2023-11-08T01:16:22.091803Z",
     "iopub.status.idle": "2023-11-08T01:16:22.130230Z",
     "shell.execute_reply": "2023-11-08T01:16:22.129546Z"
    },
    "id": "_tSUm4yAVIif"
   },
   "outputs": [],
   "source": [
    "initial_weights = os.path.join(tempfile.mkdtemp(),'initial_weights')\n",
    "model.save_weights(initial_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EVXiLyqyZ8AX"
   },
   "source": [
    "### 确认偏差修正有帮助\n",
    "\n",
    "在继续之前，迅速确认这一细致偏差初始化是否确实起了作用。\n",
    "\n",
    "在使用和不使用此细致初始化的情况下，将模型训练 20 个周期，并比较损失： "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:22.134725Z",
     "iopub.status.busy": "2023-11-08T01:16:22.134126Z",
     "iopub.status.idle": "2023-11-08T01:16:33.681852Z",
     "shell.execute_reply": "2023-11-08T01:16:33.680955Z"
    },
    "id": "Dm4-4K5RZ63Q"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1699406183.892374  943342 device_compiler.h:186] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.\n"
     ]
    }
   ],
   "source": [
    "model = make_model()\n",
    "model.load_weights(initial_weights)\n",
    "model.layers[-1].bias.assign([0.0])\n",
    "zero_bias_history = model.fit(\n",
    "    train_features,\n",
    "    train_labels,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    epochs=20,\n",
    "    validation_data=(val_features, val_labels), \n",
    "    verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:33.686462Z",
     "iopub.status.busy": "2023-11-08T01:16:33.685832Z",
     "iopub.status.idle": "2023-11-08T01:16:45.146730Z",
     "shell.execute_reply": "2023-11-08T01:16:45.145884Z"
    },
    "id": "j8DsLXHQaSql"
   },
   "outputs": [],
   "source": [
    "model = make_model()\n",
    "model.load_weights(initial_weights)\n",
    "careful_bias_history = model.fit(\n",
    "    train_features,\n",
    "    train_labels,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    epochs=20,\n",
    "    validation_data=(val_features, val_labels), \n",
    "    verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:45.151507Z",
     "iopub.status.busy": "2023-11-08T01:16:45.150723Z",
     "iopub.status.idle": "2023-11-08T01:16:45.156102Z",
     "shell.execute_reply": "2023-11-08T01:16:45.155127Z"
    },
    "id": "E3XsMBjhauFV"
   },
   "outputs": [],
   "source": [
    "def plot_loss(history, label, n):\n",
    "  # Use a log scale to show the wide range of values.\n",
    "  plt.semilogy(history.epoch,  history.history['loss'],\n",
    "               color=colors[n], label='Train '+label)\n",
    "  plt.semilogy(history.epoch,  history.history['val_loss'],\n",
    "          color=colors[n], label='Val '+label,\n",
    "          linestyle=\"--\")\n",
    "  plt.xlabel('Epoch')\n",
    "  plt.ylabel('Loss')\n",
    "  \n",
    "  plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:45.159673Z",
     "iopub.status.busy": "2023-11-08T01:16:45.158973Z",
     "iopub.status.idle": "2023-11-08T01:16:45.575707Z",
     "shell.execute_reply": "2023-11-08T01:16:45.574992Z"
    },
    "id": "dxFaskm7beC7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_loss(zero_bias_history, \"Zero Bias\", 0)\n",
    "plot_loss(careful_bias_history, \"Careful Bias\", 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fKMioV0ddG3R"
   },
   "source": [
    "上图清楚表明：就验证损失而言，在这个问题上，此细致初始化具有明显优势。 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RsA_7SEntRaV"
   },
   "source": [
    "### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:16:45.580414Z",
     "iopub.status.busy": "2023-11-08T01:16:45.579669Z",
     "iopub.status.idle": "2023-11-08T01:17:17.017606Z",
     "shell.execute_reply": "2023-11-08T01:17:17.016806Z"
    },
    "id": "yZKAc8NCDnoR"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 2:12 - loss: 0.0222 - tp: 53.0000 - fp: 7.0000 - tn: 47537.0000 - fn: 20.0000 - accuracy: 0.9994 - precision: 0.8833 - recall: 0.7260 - auc: 0.9381 - prc: 0.8214"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0163 - tp: 54.0000 - fp: 9.0000 - tn: 72074.0000 - fn: 56.0000 - accuracy: 0.9991 - precision: 0.8571 - recall: 0.4909 - auc: 0.8165 - prc: 0.5668  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0152 - tp: 57.0000 - fp: 9.0000 - tn: 98651.0000 - fn: 100.0000 - accuracy: 0.9989 - precision: 0.8636 - recall: 0.3631 - auc: 0.7679 - prc: 0.4679"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0148 - tp: 62.0000 - fp: 13.0000 - tn: 125224.0000 - fn: 142.0000 - accuracy: 0.9988 - precision: 0.8267 - recall: 0.3039 - auc: 0.7463 - prc: 0.4043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.0142 - tp: 70.0000 - fp: 15.0000 - tn: 149753.0000 - fn: 179.0000 - accuracy: 0.9987 - precision: 0.8235 - recall: 0.2811 - auc: 0.7429 - prc: 0.3902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.0138 - tp: 81.0000 - fp: 20.0000 - tn: 174282.0000 - fn: 210.0000 - accuracy: 0.9987 - precision: 0.8020 - recall: 0.2784 - auc: 0.7343 - prc: 0.3645"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.0140 - tp: 92.0000 - fp: 23.0000 - tn: 198804.0000 - fn: 250.0000 - accuracy: 0.9986 - precision: 0.8000 - recall: 0.2690 - auc: 0.7217 - prc: 0.3359"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "88/90 [============================>.] - ETA: 0s - loss: 0.0136 - tp: 101.0000 - fp: 26.0000 - tn: 225385.0000 - fn: 281.0000 - accuracy: 0.9986 - precision: 0.7953 - recall: 0.2644 - auc: 0.7225 - prc: 0.3209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 3s 12ms/step - loss: 0.0135 - tp: 101.0000 - fp: 26.0000 - tn: 227434.0000 - fn: 284.0000 - accuracy: 0.9986 - precision: 0.7953 - recall: 0.2623 - auc: 0.7220 - prc: 0.3198 - val_loss: 0.0076 - val_tp: 3.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 66.0000 - val_accuracy: 0.9984 - val_precision: 0.3750 - val_recall: 0.0435 - val_auc: 0.8258 - val_prc: 0.4747\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0013 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0109 - tp: 14.0000 - fp: 3.0000 - tn: 28613.0000 - fn: 42.0000 - accuracy: 0.9984 - precision: 0.8235 - recall: 0.2500 - auc: 0.7258 - prc: 0.3564     "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0092 - tp: 32.0000 - fp: 5.0000 - tn: 55193.0000 - fn: 66.0000 - accuracy: 0.9987 - precision: 0.8649 - recall: 0.3265 - auc: 0.7647 - prc: 0.4089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0091 - tp: 47.0000 - fp: 9.0000 - tn: 81768.0000 - fn: 96.0000 - accuracy: 0.9987 - precision: 0.8393 - recall: 0.3287 - auc: 0.7632 - prc: 0.3912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0093 - tp: 62.0000 - fp: 12.0000 - tn: 108343.0000 - fn: 127.0000 - accuracy: 0.9987 - precision: 0.8378 - recall: 0.3280 - auc: 0.7559 - prc: 0.3724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0093 - tp: 74.0000 - fp: 14.0000 - tn: 134924.0000 - fn: 156.0000 - accuracy: 0.9987 - precision: 0.8409 - recall: 0.3217 - auc: 0.7502 - prc: 0.3541"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0094 - tp: 90.0000 - fp: 15.0000 - tn: 161500.0000 - fn: 187.0000 - accuracy: 0.9988 - precision: 0.8571 - recall: 0.3249 - auc: 0.7463 - prc: 0.3554"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0094 - tp: 98.0000 - fp: 16.0000 - tn: 181944.0000 - fn: 218.0000 - accuracy: 0.9987 - precision: 0.8596 - recall: 0.3101 - auc: 0.7451 - prc: 0.3475 - val_loss: 0.0050 - val_tp: 18.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 51.0000 - val_accuracy: 0.9987 - val_precision: 0.7500 - val_recall: 0.2609 - val_auc: 0.9127 - val_prc: 0.6222\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0169 - tp: 1.0000 - fp: 1.0000 - tn: 2040.0000 - fn: 6.0000 - accuracy: 0.9966 - precision: 0.5000 - recall: 0.1429 - auc: 0.7811 - prc: 0.3493"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0084 - tp: 12.0000 - fp: 4.0000 - tn: 26574.0000 - fn: 34.0000 - accuracy: 0.9986 - precision: 0.7500 - recall: 0.2609 - auc: 0.8100 - prc: 0.3670"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0082 - tp: 21.0000 - fp: 7.0000 - tn: 53161.0000 - fn: 59.0000 - accuracy: 0.9988 - precision: 0.7500 - recall: 0.2625 - auc: 0.7694 - prc: 0.2973"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0069 - tp: 39.0000 - fp: 9.0000 - tn: 79748.0000 - fn: 76.0000 - accuracy: 0.9989 - precision: 0.8125 - recall: 0.3391 - auc: 0.8085 - prc: 0.4113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0075 - tp: 67.0000 - fp: 12.0000 - tn: 106300.0000 - fn: 117.0000 - accuracy: 0.9988 - precision: 0.8481 - recall: 0.3641 - auc: 0.8303 - prc: 0.4824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0078 - tp: 81.0000 - fp: 16.0000 - tn: 132874.0000 - fn: 149.0000 - accuracy: 0.9988 - precision: 0.8351 - recall: 0.3522 - auc: 0.8242 - prc: 0.4642"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0078 - tp: 105.0000 - fp: 21.0000 - tn: 159444.0000 - fn: 174.0000 - accuracy: 0.9988 - precision: 0.8333 - recall: 0.3763 - auc: 0.8294 - prc: 0.4714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.0079 - tp: 118.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 198.0000 - accuracy: 0.9988 - precision: 0.8252 - recall: 0.3734 - auc: 0.8315 - prc: 0.4644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0079 - tp: 118.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 198.0000 - accuracy: 0.9988 - precision: 0.8252 - recall: 0.3734 - auc: 0.8315 - prc: 0.4644 - val_loss: 0.0039 - val_tp: 38.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 31.0000 - val_accuracy: 0.9992 - val_precision: 0.8636 - val_recall: 0.5507 - val_auc: 0.9199 - val_prc: 0.6663\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0117 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 4.0000 - accuracy: 0.9980 - precision: 1.0000 - recall: 0.2000 - auc: 0.7963 - prc: 0.4049"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0068 - tp: 20.0000 - fp: 2.0000 - tn: 26577.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.9091 - recall: 0.4444 - auc: 0.8411 - prc: 0.5325 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.0060 - tp: 44.0000 - fp: 4.0000 - tn: 51106.0000 - fn: 46.0000 - accuracy: 0.9990 - precision: 0.9167 - recall: 0.4889 - auc: 0.8640 - prc: 0.6129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.0066 - tp: 63.0000 - fp: 8.0000 - tn: 75635.0000 - fn: 70.0000 - accuracy: 0.9990 - precision: 0.8873 - recall: 0.4737 - auc: 0.8507 - prc: 0.5687"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.0064 - tp: 75.0000 - fp: 8.0000 - tn: 100172.0000 - fn: 97.0000 - accuracy: 0.9990 - precision: 0.9036 - recall: 0.4360 - auc: 0.8548 - prc: 0.5621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 0.0064 - tp: 98.0000 - fp: 11.0000 - tn: 124703.0000 - fn: 116.0000 - accuracy: 0.9990 - precision: 0.8991 - recall: 0.4579 - auc: 0.8548 - prc: 0.5553"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "74/90 [=======================>......] - ETA: 0s - loss: 0.0066 - tp: 116.0000 - fp: 16.0000 - tn: 151273.0000 - fn: 147.0000 - accuracy: 0.9989 - precision: 0.8788 - recall: 0.4411 - auc: 0.8547 - prc: 0.5462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.0069 - tp: 130.0000 - fp: 24.0000 - tn: 177845.0000 - fn: 177.0000 - accuracy: 0.9989 - precision: 0.8442 - recall: 0.4235 - auc: 0.8540 - prc: 0.5259"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0069 - tp: 132.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 184.0000 - accuracy: 0.9989 - precision: 0.8408 - recall: 0.4177 - auc: 0.8565 - prc: 0.5263 - val_loss: 0.0036 - val_tp: 43.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 26.0000 - val_accuracy: 0.9993 - val_precision: 0.8776 - val_recall: 0.6232 - val_auc: 0.9272 - val_prc: 0.6980\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0048 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 0.7462 - prc: 0.5013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0075 - tp: 14.0000 - fp: 5.0000 - tn: 26572.0000 - fn: 33.0000 - accuracy: 0.9986 - precision: 0.7368 - recall: 0.2979 - auc: 0.8160 - prc: 0.4588 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.0073 - tp: 39.0000 - fp: 8.0000 - tn: 51095.0000 - fn: 58.0000 - accuracy: 0.9987 - precision: 0.8298 - recall: 0.4021 - auc: 0.8428 - prc: 0.5501"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.0074 - tp: 55.0000 - fp: 11.0000 - tn: 77668.0000 - fn: 90.0000 - accuracy: 0.9987 - precision: 0.8333 - recall: 0.3793 - auc: 0.8494 - prc: 0.5448"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.0072 - tp: 82.0000 - fp: 14.0000 - tn: 104239.0000 - fn: 113.0000 - accuracy: 0.9988 - precision: 0.8542 - recall: 0.4205 - auc: 0.8516 - prc: 0.5607"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.0068 - tp: 97.0000 - fp: 19.0000 - tn: 128775.0000 - fn: 133.0000 - accuracy: 0.9988 - precision: 0.8362 - recall: 0.4217 - auc: 0.8632 - prc: 0.5676"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.0066 - tp: 117.0000 - fp: 23.0000 - tn: 153306.0000 - fn: 154.0000 - accuracy: 0.9988 - precision: 0.8357 - recall: 0.4317 - auc: 0.8633 - prc: 0.5670"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.0065 - tp: 136.0000 - fp: 27.0000 - tn: 177839.0000 - fn: 174.0000 - accuracy: 0.9989 - precision: 0.8344 - recall: 0.4387 - auc: 0.8641 - prc: 0.5668"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0065 - tp: 138.0000 - fp: 28.0000 - tn: 181932.0000 - fn: 178.0000 - accuracy: 0.9989 - precision: 0.8313 - recall: 0.4367 - auc: 0.8619 - prc: 0.5629 - val_loss: 0.0034 - val_tp: 44.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 25.0000 - val_accuracy: 0.9993 - val_precision: 0.8800 - val_recall: 0.6377 - val_auc: 0.9345 - val_prc: 0.7071\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0121 - tp: 1.0000 - fp: 1.0000 - tn: 2041.0000 - fn: 5.0000 - accuracy: 0.9971 - precision: 0.5000 - recall: 0.1667 - auc: 0.8308 - prc: 0.4015"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0081 - tp: 23.0000 - fp: 8.0000 - tn: 28607.0000 - fn: 34.0000 - accuracy: 0.9985 - precision: 0.7419 - recall: 0.4035 - auc: 0.8579 - prc: 0.5129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0076 - tp: 51.0000 - fp: 14.0000 - tn: 55177.0000 - fn: 54.0000 - accuracy: 0.9988 - precision: 0.7846 - recall: 0.4857 - auc: 0.8746 - prc: 0.5408"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0070 - tp: 76.0000 - fp: 16.0000 - tn: 81748.0000 - fn: 80.0000 - accuracy: 0.9988 - precision: 0.8261 - recall: 0.4872 - auc: 0.8767 - prc: 0.5825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0064 - tp: 94.0000 - fp: 18.0000 - tn: 108333.0000 - fn: 99.0000 - accuracy: 0.9989 - precision: 0.8393 - recall: 0.4870 - auc: 0.8741 - prc: 0.5848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0064 - tp: 104.0000 - fp: 23.0000 - tn: 134911.0000 - fn: 130.0000 - accuracy: 0.9989 - precision: 0.8189 - recall: 0.4444 - auc: 0.8681 - prc: 0.5673"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0063 - tp: 127.0000 - fp: 23.0000 - tn: 161487.0000 - fn: 155.0000 - accuracy: 0.9989 - precision: 0.8467 - recall: 0.4504 - auc: 0.8690 - prc: 0.5785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0061 - tp: 149.0000 - fp: 29.0000 - tn: 181931.0000 - fn: 167.0000 - accuracy: 0.9989 - precision: 0.8371 - recall: 0.4715 - auc: 0.8767 - prc: 0.5928 - val_loss: 0.0032 - val_tp: 44.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 25.0000 - val_accuracy: 0.9993 - val_precision: 0.8800 - val_recall: 0.6377 - val_auc: 0.9417 - val_prc: 0.7401\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0043 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.9945 - prc: 0.1866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0054 - tp: 18.0000 - fp: 3.0000 - tn: 26578.0000 - fn: 25.0000 - accuracy: 0.9989 - precision: 0.8571 - recall: 0.4186 - auc: 0.9056 - prc: 0.6345             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0065 - tp: 49.0000 - fp: 6.0000 - tn: 53136.0000 - fn: 57.0000 - accuracy: 0.9988 - precision: 0.8909 - recall: 0.4623 - auc: 0.8616 - prc: 0.6259"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0063 - tp: 63.0000 - fp: 12.0000 - tn: 79717.0000 - fn: 80.0000 - accuracy: 0.9988 - precision: 0.8400 - recall: 0.4406 - auc: 0.8514 - prc: 0.5675"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0066 - tp: 87.0000 - fp: 17.0000 - tn: 106287.0000 - fn: 105.0000 - accuracy: 0.9989 - precision: 0.8365 - recall: 0.4531 - auc: 0.8524 - prc: 0.5459"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0067 - tp: 111.0000 - fp: 20.0000 - tn: 132860.0000 - fn: 129.0000 - accuracy: 0.9989 - precision: 0.8473 - recall: 0.4625 - auc: 0.8504 - prc: 0.5494"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0065 - tp: 132.0000 - fp: 25.0000 - tn: 159431.0000 - fn: 156.0000 - accuracy: 0.9989 - precision: 0.8408 - recall: 0.4583 - auc: 0.8577 - prc: 0.5599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0061 - tp: 150.0000 - fp: 29.0000 - tn: 181931.0000 - fn: 166.0000 - accuracy: 0.9989 - precision: 0.8380 - recall: 0.4747 - auc: 0.8655 - prc: 0.5760 - val_loss: 0.0031 - val_tp: 44.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 25.0000 - val_accuracy: 0.9993 - val_precision: 0.8800 - val_recall: 0.6377 - val_auc: 0.9418 - val_prc: 0.7652\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0048 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.8312 - prc: 0.6682"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0045 - tp: 25.0000 - fp: 4.0000 - tn: 28621.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8621 - recall: 0.5319 - auc: 0.9140 - prc: 0.6962             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0048 - tp: 44.0000 - fp: 6.0000 - tn: 55198.0000 - fn: 48.0000 - accuracy: 0.9990 - precision: 0.8800 - recall: 0.4783 - auc: 0.8957 - prc: 0.6812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0049 - tp: 66.0000 - fp: 11.0000 - tn: 81777.0000 - fn: 66.0000 - accuracy: 0.9991 - precision: 0.8571 - recall: 0.5000 - auc: 0.8891 - prc: 0.6565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0055 - tp: 88.0000 - fp: 13.0000 - tn: 106301.0000 - fn: 94.0000 - accuracy: 0.9990 - precision: 0.8713 - recall: 0.4835 - auc: 0.8807 - prc: 0.6367"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0062 - tp: 107.0000 - fp: 19.0000 - tn: 132872.0000 - fn: 122.0000 - accuracy: 0.9989 - precision: 0.8492 - recall: 0.4672 - auc: 0.8655 - prc: 0.5871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0061 - tp: 123.0000 - fp: 21.0000 - tn: 159450.0000 - fn: 150.0000 - accuracy: 0.9989 - precision: 0.8542 - recall: 0.4505 - auc: 0.8668 - prc: 0.5788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0061 - tp: 144.0000 - fp: 22.0000 - tn: 181938.0000 - fn: 172.0000 - accuracy: 0.9989 - precision: 0.8675 - recall: 0.4557 - auc: 0.8658 - prc: 0.5889 - val_loss: 0.0029 - val_tp: 45.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 24.0000 - val_accuracy: 0.9993 - val_precision: 0.8824 - val_recall: 0.6522 - val_auc: 0.9418 - val_prc: 0.7871\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 7.6812e-04 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0047 - tp: 30.0000 - fp: 5.0000 - tn: 28611.0000 - fn: 26.0000 - accuracy: 0.9989 - precision: 0.8571 - recall: 0.5357 - auc: 0.9188 - prc: 0.7594         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0060 - tp: 49.0000 - fp: 8.0000 - tn: 55187.0000 - fn: 52.0000 - accuracy: 0.9989 - precision: 0.8596 - recall: 0.4851 - auc: 0.8650 - prc: 0.6163"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0060 - tp: 70.0000 - fp: 13.0000 - tn: 81761.0000 - fn: 76.0000 - accuracy: 0.9989 - precision: 0.8434 - recall: 0.4795 - auc: 0.8616 - prc: 0.5926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0060 - tp: 90.0000 - fp: 16.0000 - tn: 108337.0000 - fn: 101.0000 - accuracy: 0.9989 - precision: 0.8491 - recall: 0.4712 - auc: 0.8572 - prc: 0.5748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0059 - tp: 116.0000 - fp: 19.0000 - tn: 134904.0000 - fn: 129.0000 - accuracy: 0.9989 - precision: 0.8593 - recall: 0.4735 - auc: 0.8640 - prc: 0.6013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0058 - tp: 136.0000 - fp: 21.0000 - tn: 159437.0000 - fn: 150.0000 - accuracy: 0.9989 - precision: 0.8662 - recall: 0.4755 - auc: 0.8658 - prc: 0.6053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0059 - tp: 144.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 172.0000 - accuracy: 0.9989 - precision: 0.8471 - recall: 0.4557 - auc: 0.8610 - prc: 0.5845 - val_loss: 0.0028 - val_tp: 46.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 23.0000 - val_accuracy: 0.9994 - val_precision: 0.8846 - val_recall: 0.6667 - val_auc: 0.9490 - val_prc: 0.8028\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0017 - tp: 1.0000 - fp: 1.0000 - tn: 2046.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.5000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0065 - tp: 18.0000 - fp: 7.0000 - tn: 26575.0000 - fn: 24.0000 - accuracy: 0.9988 - precision: 0.7200 - recall: 0.4286 - auc: 0.8556 - prc: 0.4701 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0056 - tp: 45.0000 - fp: 11.0000 - tn: 53149.0000 - fn: 43.0000 - accuracy: 0.9990 - precision: 0.8036 - recall: 0.5114 - auc: 0.8680 - prc: 0.5832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0058 - tp: 62.0000 - fp: 20.0000 - tn: 79724.0000 - fn: 66.0000 - accuracy: 0.9989 - precision: 0.7561 - recall: 0.4844 - auc: 0.8659 - prc: 0.5632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0057 - tp: 81.0000 - fp: 24.0000 - tn: 106303.0000 - fn: 88.0000 - accuracy: 0.9989 - precision: 0.7714 - recall: 0.4793 - auc: 0.8716 - prc: 0.5663"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0059 - tp: 97.0000 - fp: 25.0000 - tn: 132874.0000 - fn: 124.0000 - accuracy: 0.9989 - precision: 0.7951 - recall: 0.4389 - auc: 0.8653 - prc: 0.5698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0058 - tp: 119.0000 - fp: 27.0000 - tn: 159450.0000 - fn: 148.0000 - accuracy: 0.9989 - precision: 0.8151 - recall: 0.4457 - auc: 0.8677 - prc: 0.5831"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0058 - tp: 144.0000 - fp: 28.0000 - tn: 181932.0000 - fn: 172.0000 - accuracy: 0.9989 - precision: 0.8372 - recall: 0.4557 - auc: 0.8690 - prc: 0.5951 - val_loss: 0.0027 - val_tp: 45.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 24.0000 - val_accuracy: 0.9993 - val_precision: 0.8824 - val_recall: 0.6522 - val_auc: 0.9490 - val_prc: 0.8107\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0074 - tp: 5.0000 - fp: 1.0000 - tn: 2041.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.8333 - recall: 0.8333 - auc: 0.9159 - prc: 0.5690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0065 - tp: 27.0000 - fp: 5.0000 - tn: 28613.0000 - fn: 27.0000 - accuracy: 0.9989 - precision: 0.8438 - recall: 0.5000 - auc: 0.8693 - prc: 0.5833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0060 - tp: 49.0000 - fp: 6.0000 - tn: 55189.0000 - fn: 52.0000 - accuracy: 0.9990 - precision: 0.8909 - recall: 0.4851 - auc: 0.8651 - prc: 0.6013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0058 - tp: 69.0000 - fp: 12.0000 - tn: 81764.0000 - fn: 75.0000 - accuracy: 0.9989 - precision: 0.8519 - recall: 0.4792 - auc: 0.8737 - prc: 0.5979"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0056 - tp: 79.0000 - fp: 14.0000 - tn: 108355.0000 - fn: 96.0000 - accuracy: 0.9990 - precision: 0.8495 - recall: 0.4514 - auc: 0.8701 - prc: 0.5820"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0057 - tp: 100.0000 - fp: 16.0000 - tn: 134932.0000 - fn: 120.0000 - accuracy: 0.9990 - precision: 0.8621 - recall: 0.4545 - auc: 0.8577 - prc: 0.5691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0058 - tp: 137.0000 - fp: 22.0000 - tn: 161492.0000 - fn: 141.0000 - accuracy: 0.9990 - precision: 0.8616 - recall: 0.4928 - auc: 0.8620 - prc: 0.5802"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0058 - tp: 150.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 166.0000 - accuracy: 0.9990 - precision: 0.8621 - recall: 0.4747 - auc: 0.8626 - prc: 0.5828 - val_loss: 0.0027 - val_tp: 45.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 24.0000 - val_accuracy: 0.9993 - val_precision: 0.8824 - val_recall: 0.6522 - val_auc: 0.9491 - val_prc: 0.8156\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0016 - tp: 3.0000 - fp: 1.0000 - tn: 2044.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.7500 - recall: 1.0000 - auc: 0.9998 - prc: 0.9041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0061 - tp: 30.0000 - fp: 7.0000 - tn: 28610.0000 - fn: 25.0000 - accuracy: 0.9989 - precision: 0.8108 - recall: 0.5455 - auc: 0.8441 - prc: 0.5886 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0052 - tp: 48.0000 - fp: 9.0000 - tn: 55192.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8421 - recall: 0.5053 - auc: 0.8673 - prc: 0.6287"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0048 - tp: 65.0000 - fp: 11.0000 - tn: 81778.0000 - fn: 66.0000 - accuracy: 0.9991 - precision: 0.8553 - recall: 0.4962 - auc: 0.8806 - prc: 0.6323"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0047 - tp: 93.0000 - fp: 17.0000 - tn: 108349.0000 - fn: 85.0000 - accuracy: 0.9991 - precision: 0.8455 - recall: 0.5225 - auc: 0.8923 - prc: 0.6563"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0051 - tp: 118.0000 - fp: 21.0000 - tn: 134916.0000 - fn: 113.0000 - accuracy: 0.9990 - precision: 0.8489 - recall: 0.5108 - auc: 0.8777 - prc: 0.6334"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0052 - tp: 137.0000 - fp: 26.0000 - tn: 161487.0000 - fn: 142.0000 - accuracy: 0.9990 - precision: 0.8405 - recall: 0.4910 - auc: 0.8806 - prc: 0.6243"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0053 - tp: 154.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 162.0000 - accuracy: 0.9990 - precision: 0.8556 - recall: 0.4873 - auc: 0.8739 - prc: 0.6229 - val_loss: 0.0026 - val_tp: 48.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 21.0000 - val_accuracy: 0.9994 - val_precision: 0.8889 - val_recall: 0.6957 - val_auc: 0.9563 - val_prc: 0.8279\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0048 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6667 - auc: 0.9160 - prc: 0.8353"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0054 - tp: 16.0000 - fp: 4.0000 - tn: 28629.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.8000 - recall: 0.4103 - auc: 0.8061 - prc: 0.5070 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0049 - tp: 42.0000 - fp: 7.0000 - tn: 55209.0000 - fn: 38.0000 - accuracy: 0.9992 - precision: 0.8571 - recall: 0.5250 - auc: 0.8362 - prc: 0.5793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0053 - tp: 62.0000 - fp: 16.0000 - tn: 81781.0000 - fn: 61.0000 - accuracy: 0.9991 - precision: 0.7949 - recall: 0.5041 - auc: 0.8484 - prc: 0.5560"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0050 - tp: 73.0000 - fp: 18.0000 - tn: 106323.0000 - fn: 82.0000 - accuracy: 0.9991 - precision: 0.8022 - recall: 0.4710 - auc: 0.8536 - prc: 0.5555"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.0052 - tp: 97.0000 - fp: 22.0000 - tn: 130843.0000 - fn: 110.0000 - accuracy: 0.9990 - precision: 0.8151 - recall: 0.4686 - auc: 0.8588 - prc: 0.5831"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.0055 - tp: 122.0000 - fp: 27.0000 - tn: 157400.0000 - fn: 147.0000 - accuracy: 0.9989 - precision: 0.8188 - recall: 0.4535 - auc: 0.8669 - prc: 0.5955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.0056 - tp: 142.0000 - fp: 28.0000 - tn: 181932.0000 - fn: 174.0000 - accuracy: 0.9989 - precision: 0.8353 - recall: 0.4494 - auc: 0.8627 - prc: 0.5919"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0056 - tp: 142.0000 - fp: 28.0000 - tn: 181932.0000 - fn: 174.0000 - accuracy: 0.9989 - precision: 0.8353 - recall: 0.4494 - auc: 0.8627 - prc: 0.5919 - val_loss: 0.0025 - val_tp: 49.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8750 - val_recall: 0.7101 - val_auc: 0.9563 - val_prc: 0.8343\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0012 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2047.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0074 - tp: 22.0000 - fp: 7.0000 - tn: 28612.0000 - fn: 31.0000 - accuracy: 0.9987 - precision: 0.7586 - recall: 0.4151 - auc: 0.8283 - prc: 0.4912             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0054 - tp: 43.0000 - fp: 8.0000 - tn: 55199.0000 - fn: 46.0000 - accuracy: 0.9990 - precision: 0.8431 - recall: 0.4831 - auc: 0.8581 - prc: 0.5858"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0048 - tp: 69.0000 - fp: 11.0000 - tn: 83827.0000 - fn: 61.0000 - accuracy: 0.9991 - precision: 0.8625 - recall: 0.5308 - auc: 0.8795 - prc: 0.6225"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "55/90 [=================>............] - ETA: 0s - loss: 0.0053 - tp: 101.0000 - fp: 14.0000 - tn: 112429.0000 - fn: 96.0000 - accuracy: 0.9990 - precision: 0.8783 - recall: 0.5127 - auc: 0.8819 - prc: 0.6226"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "69/90 [======================>.......] - ETA: 0s - loss: 0.0057 - tp: 132.0000 - fp: 18.0000 - tn: 141030.0000 - fn: 132.0000 - accuracy: 0.9989 - precision: 0.8800 - recall: 0.5000 - auc: 0.8756 - prc: 0.6215"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "82/90 [==========================>...] - ETA: 0s - loss: 0.0055 - tp: 150.0000 - fp: 24.0000 - tn: 167612.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8621 - recall: 0.5000 - auc: 0.8787 - prc: 0.6158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 6ms/step - loss: 0.0054 - tp: 155.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 161.0000 - accuracy: 0.9990 - precision: 0.8611 - recall: 0.4905 - auc: 0.8752 - prc: 0.6058 - val_loss: 0.0024 - val_tp: 51.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8644 - val_recall: 0.7391 - val_auc: 0.9563 - val_prc: 0.8385\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0143 - tp: 3.0000 - fp: 1.0000 - tn: 2041.0000 - fn: 3.0000 - accuracy: 0.9980 - precision: 0.7500 - recall: 0.5000 - auc: 0.7469 - prc: 0.3884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0051 - tp: 34.0000 - fp: 5.0000 - tn: 30656.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.8718 - recall: 0.5763 - auc: 0.8888 - prc: 0.7132"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "29/90 [========>.....................] - ETA: 0s - loss: 0.0063 - tp: 62.0000 - fp: 15.0000 - tn: 59258.0000 - fn: 57.0000 - accuracy: 0.9988 - precision: 0.8052 - recall: 0.5210 - auc: 0.8938 - prc: 0.6216"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "43/90 [=============>................] - ETA: 0s - loss: 0.0062 - tp: 81.0000 - fp: 19.0000 - tn: 87879.0000 - fn: 85.0000 - accuracy: 0.9988 - precision: 0.8100 - recall: 0.4880 - auc: 0.8782 - prc: 0.5892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "57/90 [==================>...........] - ETA: 0s - loss: 0.0059 - tp: 100.0000 - fp: 24.0000 - tn: 116505.0000 - fn: 107.0000 - accuracy: 0.9989 - precision: 0.8065 - recall: 0.4831 - auc: 0.8755 - prc: 0.5848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "70/90 [======================>.......] - ETA: 0s - loss: 0.0058 - tp: 130.0000 - fp: 26.0000 - tn: 143074.0000 - fn: 130.0000 - accuracy: 0.9989 - precision: 0.8333 - recall: 0.5000 - auc: 0.8737 - prc: 0.6053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "83/90 [==========================>...] - ETA: 0s - loss: 0.0054 - tp: 149.0000 - fp: 29.0000 - tn: 169660.0000 - fn: 146.0000 - accuracy: 0.9990 - precision: 0.8371 - recall: 0.5051 - auc: 0.8750 - prc: 0.6190"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 6ms/step - loss: 0.0054 - tp: 160.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 156.0000 - accuracy: 0.9990 - precision: 0.8421 - recall: 0.5063 - auc: 0.8722 - prc: 0.6190 - val_loss: 0.0024 - val_tp: 50.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8772 - val_recall: 0.7246 - val_auc: 0.9563 - val_prc: 0.8455\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0061 - tp: 1.0000 - fp: 1.0000 - tn: 2045.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.5000 - recall: 0.5000 - auc: 0.9961 - prc: 0.2938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0044 - tp: 21.0000 - fp: 6.0000 - tn: 26578.0000 - fn: 19.0000 - accuracy: 0.9991 - precision: 0.7778 - recall: 0.5250 - auc: 0.8989 - prc: 0.6050"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0044 - tp: 44.0000 - fp: 11.0000 - tn: 53156.0000 - fn: 37.0000 - accuracy: 0.9991 - precision: 0.8000 - recall: 0.5432 - auc: 0.8940 - prc: 0.6204"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0049 - tp: 63.0000 - fp: 12.0000 - tn: 79733.0000 - fn: 64.0000 - accuracy: 0.9990 - precision: 0.8400 - recall: 0.4961 - auc: 0.8650 - prc: 0.5994"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0052 - tp: 88.0000 - fp: 16.0000 - tn: 106299.0000 - fn: 93.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.4862 - auc: 0.8718 - prc: 0.6113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0054 - tp: 119.0000 - fp: 20.0000 - tn: 132866.0000 - fn: 115.0000 - accuracy: 0.9990 - precision: 0.8561 - recall: 0.5085 - auc: 0.8793 - prc: 0.6189"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0053 - tp: 135.0000 - fp: 24.0000 - tn: 159443.0000 - fn: 142.0000 - accuracy: 0.9990 - precision: 0.8491 - recall: 0.4874 - auc: 0.8744 - prc: 0.6138"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0053 - tp: 155.0000 - fp: 29.0000 - tn: 181931.0000 - fn: 161.0000 - accuracy: 0.9990 - precision: 0.8424 - recall: 0.4905 - auc: 0.8787 - prc: 0.6159 - val_loss: 0.0023 - val_tp: 50.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8772 - val_recall: 0.7246 - val_auc: 0.9563 - val_prc: 0.8522\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0099 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 4.0000 - accuracy: 0.9980 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.7482 - prc: 0.5028"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0044 - tp: 25.0000 - fp: 3.0000 - tn: 28621.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.8929 - recall: 0.5208 - auc: 0.8740 - prc: 0.6697             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0044 - tp: 57.0000 - fp: 8.0000 - tn: 55190.0000 - fn: 41.0000 - accuracy: 0.9991 - precision: 0.8769 - recall: 0.5816 - auc: 0.8970 - prc: 0.6821"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0051 - tp: 82.0000 - fp: 14.0000 - tn: 81756.0000 - fn: 68.0000 - accuracy: 0.9990 - precision: 0.8542 - recall: 0.5467 - auc: 0.8788 - prc: 0.6432"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0053 - tp: 105.0000 - fp: 19.0000 - tn: 108328.0000 - fn: 92.0000 - accuracy: 0.9990 - precision: 0.8468 - recall: 0.5330 - auc: 0.8770 - prc: 0.6191"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0049 - tp: 125.0000 - fp: 23.0000 - tn: 134917.0000 - fn: 103.0000 - accuracy: 0.9991 - precision: 0.8446 - recall: 0.5482 - auc: 0.8761 - prc: 0.6229"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0052 - tp: 150.0000 - fp: 33.0000 - tn: 161485.0000 - fn: 124.0000 - accuracy: 0.9990 - precision: 0.8197 - recall: 0.5474 - auc: 0.8747 - prc: 0.6076"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0052 - tp: 172.0000 - fp: 35.0000 - tn: 181925.0000 - fn: 144.0000 - accuracy: 0.9990 - precision: 0.8309 - recall: 0.5443 - auc: 0.8802 - prc: 0.6151 - val_loss: 0.0023 - val_tp: 47.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 22.0000 - val_accuracy: 0.9994 - val_precision: 0.8868 - val_recall: 0.6812 - val_auc: 0.9563 - val_prc: 0.8593\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0186 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2040.0000 - fn: 7.0000 - accuracy: 0.9966 - precision: 1.0000 - recall: 0.1250 - auc: 0.7482 - prc: 0.4241"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0070 - tp: 24.0000 - fp: 3.0000 - tn: 28612.0000 - fn: 33.0000 - accuracy: 0.9987 - precision: 0.8889 - recall: 0.4211 - auc: 0.8409 - prc: 0.5660 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0067 - tp: 43.0000 - fp: 10.0000 - tn: 55181.0000 - fn: 62.0000 - accuracy: 0.9987 - precision: 0.8113 - recall: 0.4095 - auc: 0.8416 - prc: 0.5411"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0062 - tp: 60.0000 - fp: 14.0000 - tn: 81759.0000 - fn: 87.0000 - accuracy: 0.9988 - precision: 0.8108 - recall: 0.4082 - auc: 0.8593 - prc: 0.5581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0059 - tp: 79.0000 - fp: 17.0000 - tn: 108334.0000 - fn: 114.0000 - accuracy: 0.9988 - precision: 0.8229 - recall: 0.4093 - auc: 0.8666 - prc: 0.5778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0059 - tp: 103.0000 - fp: 20.0000 - tn: 134905.0000 - fn: 140.0000 - accuracy: 0.9988 - precision: 0.8374 - recall: 0.4239 - auc: 0.8670 - prc: 0.5854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0057 - tp: 123.0000 - fp: 23.0000 - tn: 161480.0000 - fn: 166.0000 - accuracy: 0.9988 - precision: 0.8425 - recall: 0.4256 - auc: 0.8655 - prc: 0.5965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0055 - tp: 138.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 178.0000 - accuracy: 0.9989 - precision: 0.8415 - recall: 0.4367 - auc: 0.8657 - prc: 0.5980 - val_loss: 0.0022 - val_tp: 50.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8772 - val_recall: 0.7246 - val_auc: 0.9563 - val_prc: 0.8602\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0017 - tp: 0.0000e+00 - fp: 1.0000 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.9995 - prc: 0.3069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0044 - tp: 20.0000 - fp: 4.0000 - tn: 28625.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.8333 - recall: 0.4651 - auc: 0.8475 - prc: 0.6322         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0044 - tp: 36.0000 - fp: 5.0000 - tn: 55211.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.8780 - recall: 0.4500 - auc: 0.8424 - prc: 0.6090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0045 - tp: 54.0000 - fp: 10.0000 - tn: 83831.0000 - fn: 73.0000 - accuracy: 0.9990 - precision: 0.8438 - recall: 0.4252 - auc: 0.8569 - prc: 0.6127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "55/90 [=================>............] - ETA: 0s - loss: 0.0048 - tp: 81.0000 - fp: 13.0000 - tn: 112450.0000 - fn: 96.0000 - accuracy: 0.9990 - precision: 0.8617 - recall: 0.4576 - auc: 0.8574 - prc: 0.6079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s - loss: 0.0049 - tp: 113.0000 - fp: 17.0000 - tn: 139018.0000 - fn: 116.0000 - accuracy: 0.9990 - precision: 0.8692 - recall: 0.4934 - auc: 0.8633 - prc: 0.6162"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "81/90 [==========================>...] - ETA: 0s - loss: 0.0053 - tp: 138.0000 - fp: 21.0000 - tn: 165580.0000 - fn: 149.0000 - accuracy: 0.9990 - precision: 0.8679 - recall: 0.4808 - auc: 0.8558 - prc: 0.5961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0055 - tp: 149.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 167.0000 - accuracy: 0.9989 - precision: 0.8514 - recall: 0.4715 - auc: 0.8546 - prc: 0.5791 - val_loss: 0.0022 - val_tp: 50.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8772 - val_recall: 0.7246 - val_auc: 0.9563 - val_prc: 0.8629\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0034 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6000 - auc: 0.9999 - prc: 0.9635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0047 - tp: 25.0000 - fp: 5.0000 - tn: 30665.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.8333 - recall: 0.5000 - auc: 0.8888 - prc: 0.6469 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/90 [========>.....................] - ETA: 0s - loss: 0.0056 - tp: 44.0000 - fp: 9.0000 - tn: 57236.0000 - fn: 55.0000 - accuracy: 0.9989 - precision: 0.8302 - recall: 0.4444 - auc: 0.8672 - prc: 0.5901"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0053 - tp: 60.0000 - fp: 12.0000 - tn: 83819.0000 - fn: 77.0000 - accuracy: 0.9989 - precision: 0.8333 - recall: 0.4380 - auc: 0.8672 - prc: 0.5865"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0053 - tp: 88.0000 - fp: 15.0000 - tn: 110379.0000 - fn: 110.0000 - accuracy: 0.9989 - precision: 0.8544 - recall: 0.4444 - auc: 0.8826 - prc: 0.6296"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s - loss: 0.0054 - tp: 115.0000 - fp: 20.0000 - tn: 138992.0000 - fn: 137.0000 - accuracy: 0.9989 - precision: 0.8519 - recall: 0.4563 - auc: 0.8797 - prc: 0.6226"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "81/90 [==========================>...] - ETA: 0s - loss: 0.0053 - tp: 134.0000 - fp: 27.0000 - tn: 165570.0000 - fn: 157.0000 - accuracy: 0.9989 - precision: 0.8323 - recall: 0.4605 - auc: 0.8801 - prc: 0.6157"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0053 - tp: 147.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 169.0000 - accuracy: 0.9989 - precision: 0.8305 - recall: 0.4652 - auc: 0.8752 - prc: 0.6042 - val_loss: 0.0021 - val_tp: 50.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8772 - val_recall: 0.7246 - val_auc: 0.9563 - val_prc: 0.8668\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0027 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0048 - tp: 33.0000 - fp: 2.0000 - tn: 30657.0000 - fn: 28.0000 - accuracy: 0.9990 - precision: 0.9429 - recall: 0.5410 - auc: 0.8924 - prc: 0.7258 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/90 [========>.....................] - ETA: 0s - loss: 0.0045 - tp: 58.0000 - fp: 6.0000 - tn: 57234.0000 - fn: 46.0000 - accuracy: 0.9991 - precision: 0.9062 - recall: 0.5577 - auc: 0.8932 - prc: 0.7011"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "42/90 [=============>................] - ETA: 0s - loss: 0.0044 - tp: 75.0000 - fp: 6.0000 - tn: 85869.0000 - fn: 66.0000 - accuracy: 0.9992 - precision: 0.9259 - recall: 0.5319 - auc: 0.8782 - prc: 0.6737"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "56/90 [=================>............] - ETA: 0s - loss: 0.0042 - tp: 102.0000 - fp: 7.0000 - tn: 114490.0000 - fn: 89.0000 - accuracy: 0.9992 - precision: 0.9358 - recall: 0.5340 - auc: 0.8863 - prc: 0.6972"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "69/90 [======================>.......] - ETA: 0s - loss: 0.0046 - tp: 124.0000 - fp: 16.0000 - tn: 141061.0000 - fn: 111.0000 - accuracy: 0.9991 - precision: 0.8857 - recall: 0.5277 - auc: 0.8796 - prc: 0.6601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "82/90 [==========================>...] - ETA: 0s - loss: 0.0048 - tp: 155.0000 - fp: 20.0000 - tn: 167622.0000 - fn: 139.0000 - accuracy: 0.9991 - precision: 0.8857 - recall: 0.5272 - auc: 0.8780 - prc: 0.6602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 6ms/step - loss: 0.0049 - tp: 164.0000 - fp: 21.0000 - tn: 181939.0000 - fn: 152.0000 - accuracy: 0.9991 - precision: 0.8865 - recall: 0.5190 - auc: 0.8737 - prc: 0.6472 - val_loss: 0.0021 - val_tp: 52.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 17.0000 - val_accuracy: 0.9995 - val_precision: 0.8814 - val_recall: 0.7536 - val_auc: 0.9563 - val_prc: 0.8674\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0040 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.3333 - auc: 0.8323 - prc: 0.6684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0060 - tp: 24.0000 - fp: 5.0000 - tn: 28609.0000 - fn: 34.0000 - accuracy: 0.9986 - precision: 0.8276 - recall: 0.4138 - auc: 0.8779 - prc: 0.6360 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/90 [========>.....................] - ETA: 0s - loss: 0.0055 - tp: 44.0000 - fp: 12.0000 - tn: 57230.0000 - fn: 58.0000 - accuracy: 0.9988 - precision: 0.7857 - recall: 0.4314 - auc: 0.8810 - prc: 0.6016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0055 - tp: 67.0000 - fp: 16.0000 - tn: 83799.0000 - fn: 86.0000 - accuracy: 0.9988 - precision: 0.8072 - recall: 0.4379 - auc: 0.8810 - prc: 0.6045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0049 - tp: 86.0000 - fp: 20.0000 - tn: 110384.0000 - fn: 102.0000 - accuracy: 0.9989 - precision: 0.8113 - recall: 0.4574 - auc: 0.8896 - prc: 0.6199"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "67/90 [=====================>........] - ETA: 0s - loss: 0.0049 - tp: 112.0000 - fp: 22.0000 - tn: 136960.0000 - fn: 122.0000 - accuracy: 0.9990 - precision: 0.8358 - recall: 0.4786 - auc: 0.8876 - prc: 0.6321"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "80/90 [=========================>....] - ETA: 0s - loss: 0.0051 - tp: 133.0000 - fp: 28.0000 - tn: 163530.0000 - fn: 149.0000 - accuracy: 0.9989 - precision: 0.8261 - recall: 0.4716 - auc: 0.8816 - prc: 0.6103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0050 - tp: 152.0000 - fp: 31.0000 - tn: 181929.0000 - fn: 164.0000 - accuracy: 0.9989 - precision: 0.8306 - recall: 0.4810 - auc: 0.8848 - prc: 0.6228 - val_loss: 0.0021 - val_tp: 53.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 16.0000 - val_accuracy: 0.9995 - val_precision: 0.8689 - val_recall: 0.7681 - val_auc: 0.9563 - val_prc: 0.8662\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 23/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0065 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.2500 - auc: 0.7482 - prc: 0.5028"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0050 - tp: 29.0000 - fp: 3.0000 - tn: 28615.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.9062 - recall: 0.5370 - auc: 0.8782 - prc: 0.6429 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0047 - tp: 51.0000 - fp: 8.0000 - tn: 55193.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.8644 - recall: 0.5368 - auc: 0.8883 - prc: 0.6528"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0048 - tp: 74.0000 - fp: 11.0000 - tn: 81768.0000 - fn: 67.0000 - accuracy: 0.9990 - precision: 0.8706 - recall: 0.5248 - auc: 0.8782 - prc: 0.6434"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0048 - tp: 94.0000 - fp: 19.0000 - tn: 108341.0000 - fn: 90.0000 - accuracy: 0.9990 - precision: 0.8319 - recall: 0.5109 - auc: 0.8873 - prc: 0.6238"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0050 - tp: 115.0000 - fp: 20.0000 - tn: 134916.0000 - fn: 117.0000 - accuracy: 0.9990 - precision: 0.8519 - recall: 0.4957 - auc: 0.8823 - prc: 0.6220"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0049 - tp: 143.0000 - fp: 26.0000 - tn: 161485.0000 - fn: 138.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.5089 - auc: 0.8849 - prc: 0.6326"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0051 - tp: 158.0000 - fp: 31.0000 - tn: 181929.0000 - fn: 158.0000 - accuracy: 0.9990 - precision: 0.8360 - recall: 0.5000 - auc: 0.8833 - prc: 0.6207 - val_loss: 0.0020 - val_tp: 51.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.9273 - val_recall: 0.7391 - val_auc: 0.9563 - val_prc: 0.8708\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0034 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 0.7484 - prc: 0.5015"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0051 - tp: 27.0000 - fp: 4.0000 - tn: 28616.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.8710 - recall: 0.5192 - auc: 0.8739 - prc: 0.6693 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0054 - tp: 48.0000 - fp: 6.0000 - tn: 55189.0000 - fn: 53.0000 - accuracy: 0.9989 - precision: 0.8889 - recall: 0.4752 - auc: 0.8701 - prc: 0.6272"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0053 - tp: 68.0000 - fp: 11.0000 - tn: 81764.0000 - fn: 77.0000 - accuracy: 0.9989 - precision: 0.8608 - recall: 0.4690 - auc: 0.8745 - prc: 0.6163"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0048 - tp: 92.0000 - fp: 14.0000 - tn: 106300.0000 - fn: 90.0000 - accuracy: 0.9990 - precision: 0.8679 - recall: 0.5055 - auc: 0.8807 - prc: 0.6342"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0048 - tp: 115.0000 - fp: 20.0000 - tn: 132877.0000 - fn: 108.0000 - accuracy: 0.9990 - precision: 0.8519 - recall: 0.5157 - auc: 0.8822 - prc: 0.6291"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0049 - tp: 142.0000 - fp: 24.0000 - tn: 159442.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8554 - recall: 0.5108 - auc: 0.8819 - prc: 0.6306"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0049 - tp: 159.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 157.0000 - accuracy: 0.9990 - precision: 0.8641 - recall: 0.5032 - auc: 0.8801 - prc: 0.6329 - val_loss: 0.0020 - val_tp: 52.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 17.0000 - val_accuracy: 0.9995 - val_precision: 0.9286 - val_recall: 0.7536 - val_auc: 0.9563 - val_prc: 0.8745\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0017 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.5000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0039 - tp: 31.0000 - fp: 5.0000 - tn: 28613.0000 - fn: 23.0000 - accuracy: 0.9990 - precision: 0.8611 - recall: 0.5741 - auc: 0.9529 - prc: 0.7724 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0039 - tp: 54.0000 - fp: 8.0000 - tn: 55190.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.8710 - recall: 0.5510 - auc: 0.9379 - prc: 0.7489"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0039 - tp: 76.0000 - fp: 9.0000 - tn: 81772.0000 - fn: 63.0000 - accuracy: 0.9991 - precision: 0.8941 - recall: 0.5468 - auc: 0.9234 - prc: 0.7308"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0045 - tp: 93.0000 - fp: 13.0000 - tn: 108349.0000 - fn: 89.0000 - accuracy: 0.9991 - precision: 0.8774 - recall: 0.5110 - auc: 0.8889 - prc: 0.6594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0047 - tp: 116.0000 - fp: 16.0000 - tn: 134924.0000 - fn: 112.0000 - accuracy: 0.9991 - precision: 0.8788 - recall: 0.5088 - auc: 0.8825 - prc: 0.6454"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0049 - tp: 137.0000 - fp: 22.0000 - tn: 161493.0000 - fn: 140.0000 - accuracy: 0.9990 - precision: 0.8616 - recall: 0.4946 - auc: 0.8832 - prc: 0.6300"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0049 - tp: 157.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 159.0000 - accuracy: 0.9990 - precision: 0.8626 - recall: 0.4968 - auc: 0.8864 - prc: 0.6369 - val_loss: 0.0020 - val_tp: 54.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 15.0000 - val_accuracy: 0.9996 - val_precision: 0.9310 - val_recall: 0.7826 - val_auc: 0.9563 - val_prc: 0.8758\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 26/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0043 - tp: 1.0000 - fp: 1.0000 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9985 - precision: 0.5000 - recall: 0.3333 - auc: 0.8320 - prc: 0.5333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0054 - tp: 17.0000 - fp: 3.0000 - tn: 28623.0000 - fn: 29.0000 - accuracy: 0.9989 - precision: 0.8500 - recall: 0.3696 - auc: 0.8464 - prc: 0.5590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0053 - tp: 38.0000 - fp: 7.0000 - tn: 55196.0000 - fn: 55.0000 - accuracy: 0.9989 - precision: 0.8444 - recall: 0.4086 - auc: 0.8589 - prc: 0.5920"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0048 - tp: 61.0000 - fp: 9.0000 - tn: 81777.0000 - fn: 73.0000 - accuracy: 0.9990 - precision: 0.8714 - recall: 0.4552 - auc: 0.8719 - prc: 0.6230"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0048 - tp: 85.0000 - fp: 11.0000 - tn: 108347.0000 - fn: 101.0000 - accuracy: 0.9990 - precision: 0.8854 - recall: 0.4570 - auc: 0.8751 - prc: 0.6362"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0047 - tp: 105.0000 - fp: 13.0000 - tn: 134929.0000 - fn: 121.0000 - accuracy: 0.9990 - precision: 0.8898 - recall: 0.4646 - auc: 0.8749 - prc: 0.6414"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0047 - tp: 138.0000 - fp: 19.0000 - tn: 161493.0000 - fn: 142.0000 - accuracy: 0.9990 - precision: 0.8790 - recall: 0.4929 - auc: 0.8792 - prc: 0.6504"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0049 - tp: 154.0000 - fp: 21.0000 - tn: 181939.0000 - fn: 162.0000 - accuracy: 0.9990 - precision: 0.8800 - recall: 0.4873 - auc: 0.8706 - prc: 0.6314 - val_loss: 0.0020 - val_tp: 55.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 14.0000 - val_accuracy: 0.9996 - val_precision: 0.9016 - val_recall: 0.7971 - val_auc: 0.9563 - val_prc: 0.8750\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 27/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.9775e-04 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2047.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0042 - tp: 19.0000 - fp: 5.0000 - tn: 28622.0000 - fn: 26.0000 - accuracy: 0.9989 - precision: 0.7917 - recall: 0.4222 - auc: 0.8990 - prc: 0.6446         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0043 - tp: 41.0000 - fp: 8.0000 - tn: 55200.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8367 - recall: 0.4659 - auc: 0.9023 - prc: 0.6465"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0051 - tp: 70.0000 - fp: 15.0000 - tn: 83809.0000 - fn: 74.0000 - accuracy: 0.9989 - precision: 0.8235 - recall: 0.4861 - auc: 0.8770 - prc: 0.6074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0052 - tp: 80.0000 - fp: 18.0000 - tn: 110388.0000 - fn: 106.0000 - accuracy: 0.9989 - precision: 0.8163 - recall: 0.4301 - auc: 0.8613 - prc: 0.5803"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "67/90 [=====================>........] - ETA: 0s - loss: 0.0050 - tp: 107.0000 - fp: 27.0000 - tn: 136957.0000 - fn: 125.0000 - accuracy: 0.9989 - precision: 0.7985 - recall: 0.4612 - auc: 0.8757 - prc: 0.6034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "80/90 [=========================>....] - ETA: 0s - loss: 0.0052 - tp: 126.0000 - fp: 31.0000 - tn: 163531.0000 - fn: 152.0000 - accuracy: 0.9989 - precision: 0.8025 - recall: 0.4532 - auc: 0.8691 - prc: 0.5927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0051 - tp: 146.0000 - fp: 33.0000 - tn: 181927.0000 - fn: 170.0000 - accuracy: 0.9989 - precision: 0.8156 - recall: 0.4620 - auc: 0.8736 - prc: 0.6080 - val_loss: 0.0019 - val_tp: 55.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 14.0000 - val_accuracy: 0.9996 - val_precision: 0.9167 - val_recall: 0.7971 - val_auc: 0.9563 - val_prc: 0.8780\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0013 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.7500 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0051 - tp: 28.0000 - fp: 2.0000 - tn: 28614.0000 - fn: 28.0000 - accuracy: 0.9990 - precision: 0.9333 - recall: 0.5000 - auc: 0.8916 - prc: 0.6614 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0054 - tp: 48.0000 - fp: 6.0000 - tn: 55193.0000 - fn: 49.0000 - accuracy: 0.9990 - precision: 0.8889 - recall: 0.4948 - auc: 0.8594 - prc: 0.5789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0049 - tp: 65.0000 - fp: 8.0000 - tn: 81782.0000 - fn: 65.0000 - accuracy: 0.9991 - precision: 0.8904 - recall: 0.5000 - auc: 0.8524 - prc: 0.5862"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0049 - tp: 93.0000 - fp: 14.0000 - tn: 108349.0000 - fn: 88.0000 - accuracy: 0.9991 - precision: 0.8692 - recall: 0.5138 - auc: 0.8633 - prc: 0.6046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0048 - tp: 119.0000 - fp: 18.0000 - tn: 134925.0000 - fn: 106.0000 - accuracy: 0.9991 - precision: 0.8686 - recall: 0.5289 - auc: 0.8742 - prc: 0.6148"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0050 - tp: 143.0000 - fp: 23.0000 - tn: 161491.0000 - fn: 135.0000 - accuracy: 0.9990 - precision: 0.8614 - recall: 0.5144 - auc: 0.8728 - prc: 0.6089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0050 - tp: 161.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 155.0000 - accuracy: 0.9990 - precision: 0.8703 - recall: 0.5095 - auc: 0.8705 - prc: 0.6133 - val_loss: 0.0019 - val_tp: 55.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 14.0000 - val_accuracy: 0.9996 - val_precision: 0.9167 - val_recall: 0.7971 - val_auc: 0.9563 - val_prc: 0.8793\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 29/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0095 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 4.0000 - accuracy: 0.9980 - precision: 1.0000 - recall: 0.3333 - auc: 0.8319 - prc: 0.6328"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0040 - tp: 17.0000 - fp: 4.0000 - tn: 28629.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8095 - recall: 0.4359 - auc: 0.8449 - prc: 0.6119 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0045 - tp: 49.0000 - fp: 5.0000 - tn: 55195.0000 - fn: 47.0000 - accuracy: 0.9991 - precision: 0.9074 - recall: 0.5104 - auc: 0.8686 - prc: 0.6806"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0041 - tp: 72.0000 - fp: 7.0000 - tn: 83825.0000 - fn: 64.0000 - accuracy: 0.9992 - precision: 0.9114 - recall: 0.5294 - auc: 0.8886 - prc: 0.6832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0042 - tp: 108.0000 - fp: 12.0000 - tn: 110390.0000 - fn: 82.0000 - accuracy: 0.9992 - precision: 0.9000 - recall: 0.5684 - auc: 0.8962 - prc: 0.7025"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "67/90 [=====================>........] - ETA: 0s - loss: 0.0046 - tp: 134.0000 - fp: 17.0000 - tn: 136954.0000 - fn: 111.0000 - accuracy: 0.9991 - precision: 0.8874 - recall: 0.5469 - auc: 0.8948 - prc: 0.6830"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "80/90 [=========================>....] - ETA: 0s - loss: 0.0045 - tp: 154.0000 - fp: 20.0000 - tn: 163537.0000 - fn: 129.0000 - accuracy: 0.9991 - precision: 0.8851 - recall: 0.5442 - auc: 0.8928 - prc: 0.6783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0045 - tp: 171.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 145.0000 - accuracy: 0.9991 - precision: 0.8769 - recall: 0.5411 - auc: 0.8912 - prc: 0.6686 - val_loss: 0.0019 - val_tp: 56.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 13.0000 - val_accuracy: 0.9996 - val_precision: 0.9180 - val_recall: 0.8116 - val_auc: 0.9563 - val_prc: 0.8791\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 30/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0070 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.8306 - prc: 0.3815"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0036 - tp: 32.0000 - fp: 1.0000 - tn: 28619.0000 - fn: 20.0000 - accuracy: 0.9993 - precision: 0.9697 - recall: 0.6154 - auc: 0.9124 - prc: 0.7680             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0040 - tp: 57.0000 - fp: 3.0000 - tn: 55190.0000 - fn: 46.0000 - accuracy: 0.9991 - precision: 0.9500 - recall: 0.5534 - auc: 0.9067 - prc: 0.7406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0042 - tp: 81.0000 - fp: 5.0000 - tn: 81766.0000 - fn: 68.0000 - accuracy: 0.9991 - precision: 0.9419 - recall: 0.5436 - auc: 0.8982 - prc: 0.7131"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 111.0000 - fp: 7.0000 - tn: 108338.0000 - fn: 88.0000 - accuracy: 0.9991 - precision: 0.9407 - recall: 0.5578 - auc: 0.8984 - prc: 0.7132"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0041 - tp: 141.0000 - fp: 11.0000 - tn: 134912.0000 - fn: 104.0000 - accuracy: 0.9991 - precision: 0.9276 - recall: 0.5755 - auc: 0.9010 - prc: 0.7185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0042 - tp: 156.0000 - fp: 14.0000 - tn: 161496.0000 - fn: 126.0000 - accuracy: 0.9991 - precision: 0.9176 - recall: 0.5532 - auc: 0.8942 - prc: 0.6972"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 173.0000 - fp: 18.0000 - tn: 181942.0000 - fn: 143.0000 - accuracy: 0.9991 - precision: 0.9058 - recall: 0.5475 - auc: 0.8928 - prc: 0.6809 - val_loss: 0.0019 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9563 - val_prc: 0.8784\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 31/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0047 - tp: 1.0000 - fp: 2.0000 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9985 - precision: 0.3333 - recall: 0.5000 - auc: 0.9993 - prc: 0.3657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0048 - tp: 24.0000 - fp: 6.0000 - tn: 26574.0000 - fn: 20.0000 - accuracy: 0.9990 - precision: 0.8000 - recall: 0.5455 - auc: 0.8965 - prc: 0.6432"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0047 - tp: 46.0000 - fp: 9.0000 - tn: 53154.0000 - fn: 39.0000 - accuracy: 0.9991 - precision: 0.8364 - recall: 0.5412 - auc: 0.8632 - prc: 0.6272"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0047 - tp: 61.0000 - fp: 12.0000 - tn: 79739.0000 - fn: 60.0000 - accuracy: 0.9991 - precision: 0.8356 - recall: 0.5041 - auc: 0.8581 - prc: 0.5916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0047 - tp: 94.0000 - fp: 19.0000 - tn: 106301.0000 - fn: 82.0000 - accuracy: 0.9991 - precision: 0.8319 - recall: 0.5341 - auc: 0.8766 - prc: 0.6362"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.0047 - tp: 118.0000 - fp: 21.0000 - tn: 130822.0000 - fn: 111.0000 - accuracy: 0.9990 - precision: 0.8489 - recall: 0.5153 - auc: 0.8831 - prc: 0.6573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.0047 - tp: 147.0000 - fp: 26.0000 - tn: 155344.0000 - fn: 131.0000 - accuracy: 0.9990 - precision: 0.8497 - recall: 0.5288 - auc: 0.8855 - prc: 0.6636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.0046 - tp: 165.0000 - fp: 30.0000 - tn: 181927.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.5238 - auc: 0.8861 - prc: 0.6550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0047 - tp: 165.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 151.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.5222 - auc: 0.8849 - prc: 0.6529 - val_loss: 0.0019 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9563 - val_prc: 0.8799\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 32/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0019 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 0.9995 - prc: 0.7123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0052 - tp: 21.0000 - fp: 7.0000 - tn: 28621.0000 - fn: 23.0000 - accuracy: 0.9990 - precision: 0.7500 - recall: 0.4773 - auc: 0.8851 - prc: 0.5134 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0046 - tp: 49.0000 - fp: 8.0000 - tn: 55200.0000 - fn: 39.0000 - accuracy: 0.9992 - precision: 0.8596 - recall: 0.5568 - auc: 0.8851 - prc: 0.6303"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0045 - tp: 82.0000 - fp: 11.0000 - tn: 81771.0000 - fn: 56.0000 - accuracy: 0.9992 - precision: 0.8817 - recall: 0.5942 - auc: 0.8827 - prc: 0.6568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0046 - tp: 103.0000 - fp: 14.0000 - tn: 108350.0000 - fn: 77.0000 - accuracy: 0.9992 - precision: 0.8803 - recall: 0.5722 - auc: 0.8736 - prc: 0.6413"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0049 - tp: 126.0000 - fp: 19.0000 - tn: 134918.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.8690 - recall: 0.5455 - auc: 0.8708 - prc: 0.6250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0048 - tp: 159.0000 - fp: 27.0000 - tn: 161479.0000 - fn: 127.0000 - accuracy: 0.9990 - precision: 0.8548 - recall: 0.5559 - auc: 0.8832 - prc: 0.6403"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0048 - tp: 173.0000 - fp: 32.0000 - tn: 181928.0000 - fn: 143.0000 - accuracy: 0.9990 - precision: 0.8439 - recall: 0.5475 - auc: 0.8846 - prc: 0.6361 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9062 - val_recall: 0.8406 - val_auc: 0.9563 - val_prc: 0.8813\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0034 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.8000 - auc: 0.8990 - prc: 0.8019"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0034 - tp: 37.0000 - fp: 5.0000 - tn: 28613.0000 - fn: 17.0000 - accuracy: 0.9992 - precision: 0.8810 - recall: 0.6852 - auc: 0.9343 - prc: 0.7839 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0043 - tp: 53.0000 - fp: 10.0000 - tn: 53142.0000 - fn: 43.0000 - accuracy: 0.9990 - precision: 0.8413 - recall: 0.5521 - auc: 0.9050 - prc: 0.6962"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0044 - tp: 79.0000 - fp: 15.0000 - tn: 79713.0000 - fn: 65.0000 - accuracy: 0.9990 - precision: 0.8404 - recall: 0.5486 - auc: 0.8980 - prc: 0.6735"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0046 - tp: 102.0000 - fp: 20.0000 - tn: 108331.0000 - fn: 91.0000 - accuracy: 0.9990 - precision: 0.8361 - recall: 0.5285 - auc: 0.8925 - prc: 0.6581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "67/90 [=====================>........] - ETA: 0s - loss: 0.0047 - tp: 129.0000 - fp: 23.0000 - tn: 136949.0000 - fn: 115.0000 - accuracy: 0.9990 - precision: 0.8487 - recall: 0.5287 - auc: 0.8839 - prc: 0.6414"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "81/90 [==========================>...] - ETA: 0s - loss: 0.0047 - tp: 152.0000 - fp: 27.0000 - tn: 165573.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8492 - recall: 0.5278 - auc: 0.8788 - prc: 0.6358"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 166.0000 - fp: 28.0000 - tn: 181932.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8557 - recall: 0.5253 - auc: 0.8799 - prc: 0.6417 - val_loss: 0.0019 - val_tp: 59.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 10.0000 - val_accuracy: 0.9996 - val_precision: 0.9077 - val_recall: 0.8551 - val_auc: 0.9563 - val_prc: 0.8787\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 34/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0083 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.5000 - auc: 0.7472 - prc: 0.5026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0037 - tp: 30.0000 - fp: 4.0000 - tn: 28624.0000 - fn: 14.0000 - accuracy: 0.9994 - precision: 0.8824 - recall: 0.6818 - auc: 0.9196 - prc: 0.6892 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0035 - tp: 59.0000 - fp: 7.0000 - tn: 53153.0000 - fn: 29.0000 - accuracy: 0.9993 - precision: 0.8939 - recall: 0.6705 - auc: 0.9196 - prc: 0.7242"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0039 - tp: 84.0000 - fp: 8.0000 - tn: 79731.0000 - fn: 49.0000 - accuracy: 0.9993 - precision: 0.9130 - recall: 0.6316 - auc: 0.8974 - prc: 0.7001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0040 - tp: 103.0000 - fp: 11.0000 - tn: 106309.0000 - fn: 73.0000 - accuracy: 0.9992 - precision: 0.9035 - recall: 0.5852 - auc: 0.8966 - prc: 0.6977"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0045 - tp: 129.0000 - fp: 19.0000 - tn: 132866.0000 - fn: 106.0000 - accuracy: 0.9991 - precision: 0.8716 - recall: 0.5489 - auc: 0.8966 - prc: 0.6655"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0047 - tp: 151.0000 - fp: 22.0000 - tn: 159440.0000 - fn: 131.0000 - accuracy: 0.9990 - precision: 0.8728 - recall: 0.5355 - auc: 0.8887 - prc: 0.6561"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 170.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 146.0000 - accuracy: 0.9991 - precision: 0.8763 - recall: 0.5380 - auc: 0.8847 - prc: 0.6515 - val_loss: 0.0019 - val_tp: 58.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9062 - val_recall: 0.8406 - val_auc: 0.9563 - val_prc: 0.8822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 35/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0126 - tp: 1.0000 - fp: 1.0000 - tn: 2043.0000 - fn: 3.0000 - accuracy: 0.9980 - precision: 0.5000 - recall: 0.2500 - auc: 0.8722 - prc: 0.2550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0050 - tp: 22.0000 - fp: 4.0000 - tn: 28621.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.4681 - auc: 0.8817 - prc: 0.5986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0046 - tp: 40.0000 - fp: 6.0000 - tn: 55200.0000 - fn: 50.0000 - accuracy: 0.9990 - precision: 0.8696 - recall: 0.4444 - auc: 0.8820 - prc: 0.6168"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0045 - tp: 64.0000 - fp: 9.0000 - tn: 81780.0000 - fn: 67.0000 - accuracy: 0.9991 - precision: 0.8767 - recall: 0.4885 - auc: 0.8726 - prc: 0.6269"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 88.0000 - fp: 15.0000 - tn: 108357.0000 - fn: 84.0000 - accuracy: 0.9991 - precision: 0.8544 - recall: 0.5116 - auc: 0.8824 - prc: 0.6485"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0046 - tp: 114.0000 - fp: 19.0000 - tn: 132875.0000 - fn: 112.0000 - accuracy: 0.9990 - precision: 0.8571 - recall: 0.5044 - auc: 0.8814 - prc: 0.6435"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0047 - tp: 145.0000 - fp: 27.0000 - tn: 159441.0000 - fn: 131.0000 - accuracy: 0.9990 - precision: 0.8430 - recall: 0.5254 - auc: 0.8845 - prc: 0.6303"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0048 - tp: 166.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8469 - recall: 0.5253 - auc: 0.8816 - prc: 0.6244 - val_loss: 0.0018 - val_tp: 56.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 13.0000 - val_accuracy: 0.9996 - val_precision: 0.9180 - val_recall: 0.8116 - val_auc: 0.9563 - val_prc: 0.8823\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 36/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0010 - tp: 2.0000 - fp: 1.0000 - tn: 2045.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.6667 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0043 - tp: 19.0000 - fp: 2.0000 - tn: 28628.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.9048 - recall: 0.4524 - auc: 0.8677 - prc: 0.6450 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0043 - tp: 42.0000 - fp: 9.0000 - tn: 55206.0000 - fn: 39.0000 - accuracy: 0.9991 - precision: 0.8235 - recall: 0.5185 - auc: 0.8814 - prc: 0.6144"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0044 - tp: 69.0000 - fp: 16.0000 - tn: 81767.0000 - fn: 68.0000 - accuracy: 0.9990 - precision: 0.8118 - recall: 0.5036 - auc: 0.8930 - prc: 0.6472"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0045 - tp: 97.0000 - fp: 21.0000 - tn: 108331.0000 - fn: 95.0000 - accuracy: 0.9989 - precision: 0.8220 - recall: 0.5052 - auc: 0.8947 - prc: 0.6629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0044 - tp: 120.0000 - fp: 22.0000 - tn: 134909.0000 - fn: 117.0000 - accuracy: 0.9990 - precision: 0.8451 - recall: 0.5063 - auc: 0.8998 - prc: 0.6760"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0045 - tp: 140.0000 - fp: 24.0000 - tn: 161483.0000 - fn: 145.0000 - accuracy: 0.9990 - precision: 0.8537 - recall: 0.4912 - auc: 0.8989 - prc: 0.6685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0045 - tp: 159.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 157.0000 - accuracy: 0.9990 - precision: 0.8548 - recall: 0.5032 - auc: 0.8976 - prc: 0.6680 - val_loss: 0.0018 - val_tp: 59.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 10.0000 - val_accuracy: 0.9996 - val_precision: 0.9077 - val_recall: 0.8551 - val_auc: 0.9564 - val_prc: 0.8842\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 37/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0053 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.2500 - auc: 0.8737 - prc: 0.6799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0040 - tp: 24.0000 - fp: 1.0000 - tn: 28624.0000 - fn: 23.0000 - accuracy: 0.9992 - precision: 0.9600 - recall: 0.5106 - auc: 0.8818 - prc: 0.6955 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0040 - tp: 54.0000 - fp: 4.0000 - tn: 55192.0000 - fn: 46.0000 - accuracy: 0.9991 - precision: 0.9310 - recall: 0.5400 - auc: 0.8990 - prc: 0.7294"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0040 - tp: 89.0000 - fp: 7.0000 - tn: 81757.0000 - fn: 67.0000 - accuracy: 0.9991 - precision: 0.9271 - recall: 0.5705 - auc: 0.9093 - prc: 0.7506"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 114.0000 - fp: 11.0000 - tn: 108335.0000 - fn: 84.0000 - accuracy: 0.9991 - precision: 0.9120 - recall: 0.5758 - auc: 0.8928 - prc: 0.7195"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0042 - tp: 135.0000 - fp: 14.0000 - tn: 134914.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.9060 - recall: 0.5625 - auc: 0.8905 - prc: 0.7055"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0043 - tp: 158.0000 - fp: 18.0000 - tn: 161491.0000 - fn: 125.0000 - accuracy: 0.9991 - precision: 0.8977 - recall: 0.5583 - auc: 0.8875 - prc: 0.6925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 177.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 139.0000 - accuracy: 0.9991 - precision: 0.8762 - recall: 0.5601 - auc: 0.8896 - prc: 0.6850 - val_loss: 0.0018 - val_tp: 59.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 10.0000 - val_accuracy: 0.9996 - val_precision: 0.9077 - val_recall: 0.8551 - val_auc: 0.9563 - val_prc: 0.8839\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 38/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0020 - tp: 3.0000 - fp: 1.0000 - tn: 2043.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.7500 - recall: 0.7500 - auc: 0.9999 - prc: 0.9442"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0033 - tp: 35.0000 - fp: 3.0000 - tn: 28619.0000 - fn: 15.0000 - accuracy: 0.9994 - precision: 0.9211 - recall: 0.7000 - auc: 0.9292 - prc: 0.7743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0050 - tp: 56.0000 - fp: 8.0000 - tn: 55185.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8750 - recall: 0.5437 - auc: 0.8725 - prc: 0.6684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0044 - tp: 78.0000 - fp: 8.0000 - tn: 81766.0000 - fn: 68.0000 - accuracy: 0.9991 - precision: 0.9070 - recall: 0.5342 - auc: 0.8859 - prc: 0.6979"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0048 - tp: 108.0000 - fp: 14.0000 - tn: 108335.0000 - fn: 87.0000 - accuracy: 0.9991 - precision: 0.8852 - recall: 0.5538 - auc: 0.8808 - prc: 0.6625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0050 - tp: 134.0000 - fp: 17.0000 - tn: 134904.0000 - fn: 113.0000 - accuracy: 0.9990 - precision: 0.8874 - recall: 0.5425 - auc: 0.8772 - prc: 0.6499"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0048 - tp: 160.0000 - fp: 21.0000 - tn: 161477.0000 - fn: 134.0000 - accuracy: 0.9990 - precision: 0.8840 - recall: 0.5442 - auc: 0.8831 - prc: 0.6621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 168.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 148.0000 - accuracy: 0.9991 - precision: 0.8750 - recall: 0.5316 - auc: 0.8832 - prc: 0.6569 - val_loss: 0.0018 - val_tp: 59.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 10.0000 - val_accuracy: 0.9996 - val_precision: 0.9077 - val_recall: 0.8551 - val_auc: 0.9563 - val_prc: 0.8821\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 39/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0010 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0063 - tp: 25.0000 - fp: 6.0000 - tn: 28612.0000 - fn: 29.0000 - accuracy: 0.9988 - precision: 0.8065 - recall: 0.4630 - auc: 0.8505 - prc: 0.5646 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0049 - tp: 50.0000 - fp: 10.0000 - tn: 55189.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8333 - recall: 0.5155 - auc: 0.8751 - prc: 0.6361"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0043 - tp: 74.0000 - fp: 13.0000 - tn: 81772.0000 - fn: 61.0000 - accuracy: 0.9991 - precision: 0.8506 - recall: 0.5481 - auc: 0.8877 - prc: 0.6632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 99.0000 - fp: 16.0000 - tn: 106301.0000 - fn: 80.0000 - accuracy: 0.9991 - precision: 0.8609 - recall: 0.5531 - auc: 0.8900 - prc: 0.6746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0041 - tp: 118.0000 - fp: 17.0000 - tn: 132886.0000 - fn: 99.0000 - accuracy: 0.9991 - precision: 0.8741 - recall: 0.5438 - auc: 0.8929 - prc: 0.6873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0045 - tp: 148.0000 - fp: 26.0000 - tn: 159444.0000 - fn: 126.0000 - accuracy: 0.9990 - precision: 0.8506 - recall: 0.5401 - auc: 0.8912 - prc: 0.6624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0047 - tp: 165.0000 - fp: 29.0000 - tn: 181931.0000 - fn: 151.0000 - accuracy: 0.9990 - precision: 0.8505 - recall: 0.5222 - auc: 0.8833 - prc: 0.6458 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9564 - val_prc: 0.8834\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 40/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0061 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.4968 - prc: 9.5103e-04"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0036 - tp: 23.0000 - fp: 5.0000 - tn: 28625.0000 - fn: 19.0000 - accuracy: 0.9992 - precision: 0.8214 - recall: 0.5476 - auc: 0.8918 - prc: 0.6769                 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0044 - tp: 45.0000 - fp: 11.0000 - tn: 55200.0000 - fn: 40.0000 - accuracy: 0.9991 - precision: 0.8036 - recall: 0.5294 - auc: 0.8812 - prc: 0.6226"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0047 - tp: 67.0000 - fp: 14.0000 - tn: 81772.0000 - fn: 67.0000 - accuracy: 0.9990 - precision: 0.8272 - recall: 0.5000 - auc: 0.8681 - prc: 0.6069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0048 - tp: 93.0000 - fp: 17.0000 - tn: 106296.0000 - fn: 90.0000 - accuracy: 0.9990 - precision: 0.8455 - recall: 0.5082 - auc: 0.8730 - prc: 0.6233"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.0049 - tp: 117.0000 - fp: 19.0000 - tn: 130825.0000 - fn: 111.0000 - accuracy: 0.9990 - precision: 0.8603 - recall: 0.5132 - auc: 0.8649 - prc: 0.6236"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.0047 - tp: 137.0000 - fp: 22.0000 - tn: 155358.0000 - fn: 131.0000 - accuracy: 0.9990 - precision: 0.8616 - recall: 0.5112 - auc: 0.8700 - prc: 0.6328"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "88/90 [============================>.] - ETA: 0s - loss: 0.0047 - tp: 158.0000 - fp: 26.0000 - tn: 179886.0000 - fn: 154.0000 - accuracy: 0.9990 - precision: 0.8587 - recall: 0.5064 - auc: 0.8802 - prc: 0.6461"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0047 - tp: 161.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 155.0000 - accuracy: 0.9990 - precision: 0.8564 - recall: 0.5095 - auc: 0.8801 - prc: 0.6468 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9564 - val_prc: 0.8841\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 41/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0141 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2040.0000 - fn: 6.0000 - accuracy: 0.9971 - precision: 1.0000 - recall: 0.2500 - auc: 0.7480 - prc: 0.5055"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0063 - tp: 24.0000 - fp: 7.0000 - tn: 28610.0000 - fn: 31.0000 - accuracy: 0.9987 - precision: 0.7742 - recall: 0.4364 - auc: 0.8072 - prc: 0.5332 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0058 - tp: 49.0000 - fp: 9.0000 - tn: 53136.0000 - fn: 54.0000 - accuracy: 0.9988 - precision: 0.8448 - recall: 0.4757 - auc: 0.8382 - prc: 0.5804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0053 - tp: 80.0000 - fp: 12.0000 - tn: 79703.0000 - fn: 77.0000 - accuracy: 0.9989 - precision: 0.8696 - recall: 0.5096 - auc: 0.8585 - prc: 0.6334"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0052 - tp: 110.0000 - fp: 19.0000 - tn: 106266.0000 - fn: 101.0000 - accuracy: 0.9989 - precision: 0.8527 - recall: 0.5213 - auc: 0.8707 - prc: 0.6571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.0049 - tp: 135.0000 - fp: 23.0000 - tn: 130797.0000 - fn: 117.0000 - accuracy: 0.9989 - precision: 0.8544 - recall: 0.5357 - auc: 0.8777 - prc: 0.6636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.0044 - tp: 153.0000 - fp: 26.0000 - tn: 157390.0000 - fn: 127.0000 - accuracy: 0.9990 - precision: 0.8547 - recall: 0.5464 - auc: 0.8809 - prc: 0.6729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.0043 - tp: 174.0000 - fp: 30.0000 - tn: 181926.0000 - fn: 142.0000 - accuracy: 0.9991 - precision: 0.8529 - recall: 0.5506 - auc: 0.8881 - prc: 0.6824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 174.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 142.0000 - accuracy: 0.9991 - precision: 0.8529 - recall: 0.5506 - auc: 0.8881 - prc: 0.6824 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9564 - val_prc: 0.8830\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 42/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0064 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6000 - auc: 0.7989 - prc: 0.6033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0040 - tp: 32.0000 - fp: 4.0000 - tn: 28614.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8889 - recall: 0.5926 - auc: 0.8972 - prc: 0.7295 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0040 - tp: 59.0000 - fp: 11.0000 - tn: 53139.0000 - fn: 39.0000 - accuracy: 0.9991 - precision: 0.8429 - recall: 0.6020 - auc: 0.9021 - prc: 0.7169"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0042 - tp: 76.0000 - fp: 12.0000 - tn: 79718.0000 - fn: 66.0000 - accuracy: 0.9990 - precision: 0.8636 - recall: 0.5352 - auc: 0.8828 - prc: 0.6896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 94.0000 - fp: 15.0000 - tn: 106301.0000 - fn: 86.0000 - accuracy: 0.9991 - precision: 0.8624 - recall: 0.5222 - auc: 0.8739 - prc: 0.6731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0043 - tp: 115.0000 - fp: 21.0000 - tn: 132875.0000 - fn: 109.0000 - accuracy: 0.9990 - precision: 0.8456 - recall: 0.5134 - auc: 0.8717 - prc: 0.6565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.0043 - tp: 139.0000 - fp: 26.0000 - tn: 157402.0000 - fn: 129.0000 - accuracy: 0.9990 - precision: 0.8424 - recall: 0.5187 - auc: 0.8758 - prc: 0.6606"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.0045 - tp: 161.0000 - fp: 27.0000 - tn: 181929.0000 - fn: 155.0000 - accuracy: 0.9990 - precision: 0.8564 - recall: 0.5095 - auc: 0.8707 - prc: 0.6479"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0045 - tp: 161.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 155.0000 - accuracy: 0.9990 - precision: 0.8564 - recall: 0.5095 - auc: 0.8707 - prc: 0.6479 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9563 - val_prc: 0.8825\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 43/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 5.8672e-04 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2047.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0036 - tp: 21.0000 - fp: 0.0000e+00 - tn: 28631.0000 - fn: 20.0000 - accuracy: 0.9993 - precision: 1.0000 - recall: 0.5122 - auc: 0.8767 - prc: 0.6612     "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0043 - tp: 50.0000 - fp: 1.0000 - tn: 53154.0000 - fn: 43.0000 - accuracy: 0.9992 - precision: 0.9804 - recall: 0.5376 - auc: 0.8750 - prc: 0.6727    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.0040 - tp: 68.0000 - fp: 5.0000 - tn: 77697.0000 - fn: 54.0000 - accuracy: 0.9992 - precision: 0.9315 - recall: 0.5574 - auc: 0.8758 - prc: 0.6504"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 85.0000 - fp: 9.0000 - tn: 104279.0000 - fn: 75.0000 - accuracy: 0.9992 - precision: 0.9043 - recall: 0.5312 - auc: 0.8675 - prc: 0.6179"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.0044 - tp: 122.0000 - fp: 14.0000 - tn: 128793.0000 - fn: 95.0000 - accuracy: 0.9992 - precision: 0.8971 - recall: 0.5622 - auc: 0.8766 - prc: 0.6406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.0047 - tp: 141.0000 - fp: 22.0000 - tn: 153318.0000 - fn: 119.0000 - accuracy: 0.9991 - precision: 0.8650 - recall: 0.5423 - auc: 0.8756 - prc: 0.6064"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.0048 - tp: 167.0000 - fp: 23.0000 - tn: 177845.0000 - fn: 141.0000 - accuracy: 0.9991 - precision: 0.8789 - recall: 0.5422 - auc: 0.8753 - prc: 0.6154"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0048 - tp: 172.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 144.0000 - accuracy: 0.9991 - precision: 0.8776 - recall: 0.5443 - auc: 0.8753 - prc: 0.6130 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8914\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 44/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0051 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.5000 - auc: 0.9162 - prc: 0.8354"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0030 - tp: 25.0000 - fp: 1.0000 - tn: 26582.0000 - fn: 16.0000 - accuracy: 0.9994 - precision: 0.9615 - recall: 0.6098 - auc: 0.9137 - prc: 0.7604 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.0038 - tp: 58.0000 - fp: 5.0000 - tn: 51105.0000 - fn: 32.0000 - accuracy: 0.9993 - precision: 0.9206 - recall: 0.6444 - auc: 0.9046 - prc: 0.7268"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.0042 - tp: 82.0000 - fp: 14.0000 - tn: 77677.0000 - fn: 51.0000 - accuracy: 0.9992 - precision: 0.8542 - recall: 0.6165 - auc: 0.8936 - prc: 0.6772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.0045 - tp: 111.0000 - fp: 19.0000 - tn: 104241.0000 - fn: 77.0000 - accuracy: 0.9991 - precision: 0.8538 - recall: 0.5904 - auc: 0.8872 - prc: 0.6711"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.0043 - tp: 134.0000 - fp: 20.0000 - tn: 128776.0000 - fn: 94.0000 - accuracy: 0.9991 - precision: 0.8701 - recall: 0.5877 - auc: 0.8871 - prc: 0.6837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.0045 - tp: 155.0000 - fp: 23.0000 - tn: 155349.0000 - fn: 121.0000 - accuracy: 0.9991 - precision: 0.8708 - recall: 0.5616 - auc: 0.8865 - prc: 0.6724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.0045 - tp: 173.0000 - fp: 30.0000 - tn: 181926.0000 - fn: 143.0000 - accuracy: 0.9991 - precision: 0.8522 - recall: 0.5475 - auc: 0.8833 - prc: 0.6598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0045 - tp: 173.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 143.0000 - accuracy: 0.9991 - precision: 0.8522 - recall: 0.5475 - auc: 0.8833 - prc: 0.6598 - val_loss: 0.0018 - val_tp: 57.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 12.0000 - val_accuracy: 0.9996 - val_precision: 0.9194 - val_recall: 0.8261 - val_auc: 0.9636 - val_prc: 0.8937\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 45/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0029 - tp: 0.0000e+00 - fp: 1.0000 - tn: 2047.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.0000e+00 - prc: 0.0000e+00"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0043 - tp: 20.0000 - fp: 3.0000 - tn: 26578.0000 - fn: 23.0000 - accuracy: 0.9990 - precision: 0.8696 - recall: 0.4651 - auc: 0.8594 - prc: 0.6600                     "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.0044 - tp: 37.0000 - fp: 5.0000 - tn: 51117.0000 - fn: 41.0000 - accuracy: 0.9991 - precision: 0.8810 - recall: 0.4744 - auc: 0.8578 - prc: 0.6205"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.0043 - tp: 64.0000 - fp: 7.0000 - tn: 77686.0000 - fn: 67.0000 - accuracy: 0.9990 - precision: 0.9014 - recall: 0.4885 - auc: 0.8730 - prc: 0.6672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.0045 - tp: 95.0000 - fp: 11.0000 - tn: 104251.0000 - fn: 91.0000 - accuracy: 0.9990 - precision: 0.8962 - recall: 0.5108 - auc: 0.8779 - prc: 0.6738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.0047 - tp: 120.0000 - fp: 18.0000 - tn: 128769.0000 - fn: 117.0000 - accuracy: 0.9990 - precision: 0.8696 - recall: 0.5063 - auc: 0.8829 - prc: 0.6693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.0046 - tp: 140.0000 - fp: 21.0000 - tn: 155348.0000 - fn: 139.0000 - accuracy: 0.9990 - precision: 0.8696 - recall: 0.5018 - auc: 0.8788 - prc: 0.6623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "88/90 [============================>.] - ETA: 0s - loss: 0.0044 - tp: 160.0000 - fp: 24.0000 - tn: 179888.0000 - fn: 152.0000 - accuracy: 0.9990 - precision: 0.8696 - recall: 0.5128 - auc: 0.8851 - prc: 0.6672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 164.0000 - fp: 24.0000 - tn: 181936.0000 - fn: 152.0000 - accuracy: 0.9990 - precision: 0.8723 - recall: 0.5190 - auc: 0.8865 - prc: 0.6724 - val_loss: 0.0018 - val_tp: 57.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 12.0000 - val_accuracy: 0.9996 - val_precision: 0.9344 - val_recall: 0.8261 - val_auc: 0.9636 - val_prc: 0.8939\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 46/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0048 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.3333 - auc: 0.8319 - prc: 0.5332"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0044 - tp: 14.0000 - fp: 3.0000 - tn: 26579.0000 - fn: 28.0000 - accuracy: 0.9988 - precision: 0.8235 - recall: 0.3333 - auc: 0.8800 - prc: 0.6353 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0042 - tp: 48.0000 - fp: 7.0000 - tn: 53148.0000 - fn: 45.0000 - accuracy: 0.9990 - precision: 0.8727 - recall: 0.5161 - auc: 0.8915 - prc: 0.6999"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.0047 - tp: 69.0000 - fp: 9.0000 - tn: 77677.0000 - fn: 69.0000 - accuracy: 0.9990 - precision: 0.8846 - recall: 0.5000 - auc: 0.8828 - prc: 0.6540"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.0048 - tp: 87.0000 - fp: 13.0000 - tn: 102213.0000 - fn: 87.0000 - accuracy: 0.9990 - precision: 0.8700 - recall: 0.5000 - auc: 0.8808 - prc: 0.6252"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.0047 - tp: 113.0000 - fp: 15.0000 - tn: 126737.0000 - fn: 111.0000 - accuracy: 0.9990 - precision: 0.8828 - recall: 0.5045 - auc: 0.8826 - prc: 0.6440"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.0044 - tp: 139.0000 - fp: 18.0000 - tn: 153316.0000 - fn: 127.0000 - accuracy: 0.9991 - precision: 0.8854 - recall: 0.5226 - auc: 0.8954 - prc: 0.6681"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.0043 - tp: 161.0000 - fp: 22.0000 - tn: 177846.0000 - fn: 147.0000 - accuracy: 0.9991 - precision: 0.8798 - recall: 0.5227 - auc: 0.8982 - prc: 0.6704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0044 - tp: 165.0000 - fp: 23.0000 - tn: 181937.0000 - fn: 151.0000 - accuracy: 0.9990 - precision: 0.8777 - recall: 0.5222 - auc: 0.8960 - prc: 0.6687 - val_loss: 0.0018 - val_tp: 59.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 10.0000 - val_accuracy: 0.9997 - val_precision: 0.9365 - val_recall: 0.8551 - val_auc: 0.9636 - val_prc: 0.8948\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 47/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0140 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2038.0000 - fn: 6.0000 - accuracy: 0.9971 - precision: 1.0000 - recall: 0.4000 - auc: 0.7977 - prc: 0.6058"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0047 - tp: 33.0000 - fp: 2.0000 - tn: 28610.0000 - fn: 27.0000 - accuracy: 0.9990 - precision: 0.9429 - recall: 0.5500 - auc: 0.8740 - prc: 0.7193 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0052 - tp: 54.0000 - fp: 7.0000 - tn: 55182.0000 - fn: 53.0000 - accuracy: 0.9989 - precision: 0.8852 - recall: 0.5047 - auc: 0.8726 - prc: 0.6391"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0049 - tp: 72.0000 - fp: 13.0000 - tn: 81763.0000 - fn: 72.0000 - accuracy: 0.9990 - precision: 0.8471 - recall: 0.5000 - auc: 0.8668 - prc: 0.6134"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0050 - tp: 95.0000 - fp: 17.0000 - tn: 106292.0000 - fn: 92.0000 - accuracy: 0.9990 - precision: 0.8482 - recall: 0.5080 - auc: 0.8624 - prc: 0.6161"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0047 - tp: 118.0000 - fp: 20.0000 - tn: 132872.0000 - fn: 110.0000 - accuracy: 0.9990 - precision: 0.8551 - recall: 0.5175 - auc: 0.8715 - prc: 0.6267"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0044 - tp: 134.0000 - fp: 22.0000 - tn: 159463.0000 - fn: 125.0000 - accuracy: 0.9991 - precision: 0.8590 - recall: 0.5174 - auc: 0.8733 - prc: 0.6284"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 166.0000 - fp: 25.0000 - tn: 181935.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8691 - recall: 0.5253 - auc: 0.8801 - prc: 0.6463 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 11.0000 - val_accuracy: 0.9997 - val_precision: 0.9355 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8953\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 48/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0017 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6667 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0046 - tp: 29.0000 - fp: 3.0000 - tn: 28615.0000 - fn: 25.0000 - accuracy: 0.9990 - precision: 0.9062 - recall: 0.5370 - auc: 0.8785 - prc: 0.6900 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0041 - tp: 57.0000 - fp: 6.0000 - tn: 55194.0000 - fn: 39.0000 - accuracy: 0.9992 - precision: 0.9048 - recall: 0.5938 - auc: 0.8791 - prc: 0.6855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0042 - tp: 85.0000 - fp: 9.0000 - tn: 81770.0000 - fn: 56.0000 - accuracy: 0.9992 - precision: 0.9043 - recall: 0.6028 - auc: 0.8783 - prc: 0.6838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 111.0000 - fp: 15.0000 - tn: 108341.0000 - fn: 77.0000 - accuracy: 0.9992 - precision: 0.8810 - recall: 0.5904 - auc: 0.8818 - prc: 0.6816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0044 - tp: 133.0000 - fp: 17.0000 - tn: 134918.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8867 - recall: 0.5708 - auc: 0.8765 - prc: 0.6711"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0044 - tp: 152.0000 - fp: 19.0000 - tn: 161499.0000 - fn: 122.0000 - accuracy: 0.9991 - precision: 0.8889 - recall: 0.5547 - auc: 0.8784 - prc: 0.6715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 169.0000 - fp: 21.0000 - tn: 181939.0000 - fn: 147.0000 - accuracy: 0.9991 - precision: 0.8895 - recall: 0.5348 - auc: 0.8738 - prc: 0.6581 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8945\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 49/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0013 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0046 - tp: 20.0000 - fp: 5.0000 - tn: 28625.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8000 - recall: 0.4762 - auc: 0.8557 - prc: 0.5958 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0047 - tp: 47.0000 - fp: 9.0000 - tn: 55196.0000 - fn: 44.0000 - accuracy: 0.9990 - precision: 0.8393 - recall: 0.5165 - auc: 0.8723 - prc: 0.6294"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0052 - tp: 77.0000 - fp: 12.0000 - tn: 81761.0000 - fn: 70.0000 - accuracy: 0.9990 - precision: 0.8652 - recall: 0.5238 - auc: 0.8626 - prc: 0.6204"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0049 - tp: 109.0000 - fp: 17.0000 - tn: 108336.0000 - fn: 82.0000 - accuracy: 0.9991 - precision: 0.8651 - recall: 0.5707 - auc: 0.8653 - prc: 0.6324"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0048 - tp: 137.0000 - fp: 19.0000 - tn: 132860.0000 - fn: 104.0000 - accuracy: 0.9991 - precision: 0.8782 - recall: 0.5685 - auc: 0.8723 - prc: 0.6556"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0048 - tp: 160.0000 - fp: 25.0000 - tn: 159430.0000 - fn: 129.0000 - accuracy: 0.9990 - precision: 0.8649 - recall: 0.5536 - auc: 0.8777 - prc: 0.6499"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0047 - tp: 173.0000 - fp: 30.0000 - tn: 181930.0000 - fn: 143.0000 - accuracy: 0.9991 - precision: 0.8522 - recall: 0.5475 - auc: 0.8786 - prc: 0.6424 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 11.0000 - val_accuracy: 0.9997 - val_precision: 0.9355 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8973\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 50/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 3.5964e-04 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0044 - tp: 24.0000 - fp: 4.0000 - tn: 28621.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.8571 - recall: 0.5106 - auc: 0.8712 - prc: 0.6086         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0048 - tp: 55.0000 - fp: 7.0000 - tn: 55183.0000 - fn: 51.0000 - accuracy: 0.9990 - precision: 0.8871 - recall: 0.5189 - auc: 0.8857 - prc: 0.6595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0038 - tp: 75.0000 - fp: 9.0000 - tn: 81777.0000 - fn: 59.0000 - accuracy: 0.9992 - precision: 0.8929 - recall: 0.5597 - auc: 0.8983 - prc: 0.6939"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0041 - tp: 100.0000 - fp: 15.0000 - tn: 108346.0000 - fn: 83.0000 - accuracy: 0.9991 - precision: 0.8696 - recall: 0.5464 - auc: 0.8952 - prc: 0.6843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0039 - tp: 127.0000 - fp: 18.0000 - tn: 134923.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8759 - recall: 0.5595 - auc: 0.9000 - prc: 0.6998"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0041 - tp: 148.0000 - fp: 20.0000 - tn: 161496.0000 - fn: 128.0000 - accuracy: 0.9991 - precision: 0.8810 - recall: 0.5362 - auc: 0.8976 - prc: 0.6934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 165.0000 - fp: 22.0000 - tn: 181938.0000 - fn: 151.0000 - accuracy: 0.9991 - precision: 0.8824 - recall: 0.5222 - auc: 0.8914 - prc: 0.6806 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8958\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 51/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0060 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.5000 - auc: 0.9159 - prc: 0.7678"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0045 - tp: 23.0000 - fp: 6.0000 - tn: 26575.0000 - fn: 20.0000 - accuracy: 0.9990 - precision: 0.7931 - recall: 0.5349 - auc: 0.8824 - prc: 0.6176 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.0045 - tp: 46.0000 - fp: 10.0000 - tn: 51104.0000 - fn: 40.0000 - accuracy: 0.9990 - precision: 0.8214 - recall: 0.5349 - auc: 0.8765 - prc: 0.6457"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.0045 - tp: 70.0000 - fp: 15.0000 - tn: 75634.0000 - fn: 57.0000 - accuracy: 0.9990 - precision: 0.8235 - recall: 0.5512 - auc: 0.8766 - prc: 0.6376"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.0043 - tp: 96.0000 - fp: 18.0000 - tn: 100163.0000 - fn: 75.0000 - accuracy: 0.9991 - precision: 0.8421 - recall: 0.5614 - auc: 0.8847 - prc: 0.6622"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.0045 - tp: 132.0000 - fp: 24.0000 - tn: 126725.0000 - fn: 95.0000 - accuracy: 0.9991 - precision: 0.8462 - recall: 0.5815 - auc: 0.8886 - prc: 0.6622"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "74/90 [=======================>......] - ETA: 0s - loss: 0.0044 - tp: 157.0000 - fp: 29.0000 - tn: 151256.0000 - fn: 110.0000 - accuracy: 0.9991 - precision: 0.8441 - recall: 0.5880 - auc: 0.8901 - prc: 0.6643"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "86/90 [===========================>..] - ETA: 0s - loss: 0.0045 - tp: 178.0000 - fp: 34.0000 - tn: 175787.0000 - fn: 129.0000 - accuracy: 0.9991 - precision: 0.8396 - recall: 0.5798 - auc: 0.8847 - prc: 0.6516"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0044 - tp: 186.0000 - fp: 35.0000 - tn: 181925.0000 - fn: 130.0000 - accuracy: 0.9991 - precision: 0.8416 - recall: 0.5886 - auc: 0.8864 - prc: 0.6577 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 3.0000 - val_tn: 45497.0000 - val_fn: 11.0000 - val_accuracy: 0.9997 - val_precision: 0.9508 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8976\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 52/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0050 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.5000 - auc: 0.9159 - prc: 0.8353"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0048 - tp: 30.0000 - fp: 6.0000 - tn: 28606.0000 - fn: 30.0000 - accuracy: 0.9987 - precision: 0.8333 - recall: 0.5000 - auc: 0.9073 - prc: 0.7165 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0052 - tp: 56.0000 - fp: 9.0000 - tn: 55173.0000 - fn: 58.0000 - accuracy: 0.9988 - precision: 0.8615 - recall: 0.4912 - auc: 0.8715 - prc: 0.6644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0050 - tp: 72.0000 - fp: 11.0000 - tn: 81756.0000 - fn: 81.0000 - accuracy: 0.9989 - precision: 0.8675 - recall: 0.4706 - auc: 0.8647 - prc: 0.6374"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0048 - tp: 93.0000 - fp: 15.0000 - tn: 110382.0000 - fn: 102.0000 - accuracy: 0.9989 - precision: 0.8611 - recall: 0.4769 - auc: 0.8705 - prc: 0.6326"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s - loss: 0.0047 - tp: 114.0000 - fp: 21.0000 - tn: 139005.0000 - fn: 124.0000 - accuracy: 0.9990 - precision: 0.8444 - recall: 0.4790 - auc: 0.8748 - prc: 0.6284"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "82/90 [==========================>...] - ETA: 0s - loss: 0.0048 - tp: 144.0000 - fp: 26.0000 - tn: 167618.0000 - fn: 148.0000 - accuracy: 0.9990 - precision: 0.8471 - recall: 0.4932 - auc: 0.8789 - prc: 0.6300"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 6ms/step - loss: 0.0048 - tp: 155.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 161.0000 - accuracy: 0.9990 - precision: 0.8516 - recall: 0.4905 - auc: 0.8769 - prc: 0.6301 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 11.0000 - val_accuracy: 0.9997 - val_precision: 0.9355 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8972\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 53/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0109 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 5.0000 - accuracy: 0.9976 - precision: 1.0000 - recall: 0.1667 - auc: 0.7479 - prc: 0.5041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0051 - tp: 24.0000 - fp: 5.0000 - tn: 28615.0000 - fn: 28.0000 - accuracy: 0.9988 - precision: 0.8276 - recall: 0.4615 - auc: 0.8639 - prc: 0.5990 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0041 - tp: 56.0000 - fp: 5.0000 - tn: 55191.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.9180 - recall: 0.5600 - auc: 0.8889 - prc: 0.6960"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0040 - tp: 79.0000 - fp: 9.0000 - tn: 81771.0000 - fn: 61.0000 - accuracy: 0.9991 - precision: 0.8977 - recall: 0.5643 - auc: 0.9026 - prc: 0.6856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0043 - tp: 107.0000 - fp: 14.0000 - tn: 108337.0000 - fn: 86.0000 - accuracy: 0.9991 - precision: 0.8843 - recall: 0.5544 - auc: 0.8953 - prc: 0.6706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0041 - tp: 132.0000 - fp: 18.0000 - tn: 134918.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8800 - recall: 0.5690 - auc: 0.8890 - prc: 0.6697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0042 - tp: 160.0000 - fp: 23.0000 - tn: 161490.0000 - fn: 119.0000 - accuracy: 0.9991 - precision: 0.8743 - recall: 0.5735 - auc: 0.8824 - prc: 0.6657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0043 - tp: 178.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 138.0000 - accuracy: 0.9991 - precision: 0.8725 - recall: 0.5633 - auc: 0.8818 - prc: 0.6617 - val_loss: 0.0017 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8960\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 54/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0025 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.8000 - auc: 0.9998 - prc: 0.9383"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0039 - tp: 25.0000 - fp: 5.0000 - tn: 28624.0000 - fn: 18.0000 - accuracy: 0.9992 - precision: 0.8333 - recall: 0.5814 - auc: 0.9172 - prc: 0.6351 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0038 - tp: 52.0000 - fp: 6.0000 - tn: 55200.0000 - fn: 38.0000 - accuracy: 0.9992 - precision: 0.8966 - recall: 0.5778 - auc: 0.9211 - prc: 0.6973"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0036 - tp: 78.0000 - fp: 6.0000 - tn: 81778.0000 - fn: 58.0000 - accuracy: 0.9992 - precision: 0.9286 - recall: 0.5735 - auc: 0.9291 - prc: 0.7341"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0040 - tp: 96.0000 - fp: 11.0000 - tn: 108351.0000 - fn: 86.0000 - accuracy: 0.9991 - precision: 0.8972 - recall: 0.5275 - auc: 0.9165 - prc: 0.6927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "66/90 [=====================>........] - ETA: 0s - loss: 0.0043 - tp: 122.0000 - fp: 17.0000 - tn: 134922.0000 - fn: 107.0000 - accuracy: 0.9991 - precision: 0.8777 - recall: 0.5328 - auc: 0.8962 - prc: 0.6625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0042 - tp: 144.0000 - fp: 18.0000 - tn: 161503.0000 - fn: 127.0000 - accuracy: 0.9991 - precision: 0.8889 - recall: 0.5314 - auc: 0.8900 - prc: 0.6657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0044 - tp: 167.0000 - fp: 21.0000 - tn: 181939.0000 - fn: 149.0000 - accuracy: 0.9991 - precision: 0.8883 - recall: 0.5285 - auc: 0.8897 - prc: 0.6597 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8952\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 55/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0069 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 4.0000 - accuracy: 0.9980 - precision: 1.0000 - recall: 0.2000 - auc: 0.8991 - prc: 0.7290"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0048 - tp: 30.0000 - fp: 3.0000 - tn: 28616.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.9091 - recall: 0.5660 - auc: 0.8857 - prc: 0.6409 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0046 - tp: 52.0000 - fp: 8.0000 - tn: 55191.0000 - fn: 45.0000 - accuracy: 0.9990 - precision: 0.8667 - recall: 0.5361 - auc: 0.8804 - prc: 0.6275"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0044 - tp: 78.0000 - fp: 12.0000 - tn: 83810.0000 - fn: 68.0000 - accuracy: 0.9990 - precision: 0.8667 - recall: 0.5342 - auc: 0.8859 - prc: 0.6405"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "55/90 [=================>............] - ETA: 0s - loss: 0.0048 - tp: 100.0000 - fp: 18.0000 - tn: 112425.0000 - fn: 97.0000 - accuracy: 0.9990 - precision: 0.8475 - recall: 0.5076 - auc: 0.8745 - prc: 0.6197"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s - loss: 0.0048 - tp: 120.0000 - fp: 22.0000 - tn: 139000.0000 - fn: 122.0000 - accuracy: 0.9990 - precision: 0.8451 - recall: 0.4959 - auc: 0.8749 - prc: 0.6134"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "81/90 [==========================>...] - ETA: 0s - loss: 0.0047 - tp: 150.0000 - fp: 24.0000 - tn: 165572.0000 - fn: 142.0000 - accuracy: 0.9990 - precision: 0.8621 - recall: 0.5137 - auc: 0.8773 - prc: 0.6350"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0046 - tp: 159.0000 - fp: 26.0000 - tn: 181934.0000 - fn: 157.0000 - accuracy: 0.9990 - precision: 0.8595 - recall: 0.5032 - auc: 0.8754 - prc: 0.6306 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9062 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8949\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 56/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0091 - tp: 3.0000 - fp: 3.0000 - tn: 2040.0000 - fn: 2.0000 - accuracy: 0.9976 - precision: 0.5000 - recall: 0.6000 - auc: 0.8985 - prc: 0.6375"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.0048 - tp: 27.0000 - fp: 6.0000 - tn: 26568.0000 - fn: 23.0000 - accuracy: 0.9989 - precision: 0.8182 - recall: 0.5400 - auc: 0.8986 - prc: 0.6369"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0042 - tp: 53.0000 - fp: 11.0000 - tn: 53146.0000 - fn: 38.0000 - accuracy: 0.9991 - precision: 0.8281 - recall: 0.5824 - auc: 0.9054 - prc: 0.6632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.0041 - tp: 83.0000 - fp: 13.0000 - tn: 79717.0000 - fn: 59.0000 - accuracy: 0.9991 - precision: 0.8646 - recall: 0.5845 - auc: 0.9144 - prc: 0.6917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.0044 - tp: 107.0000 - fp: 16.0000 - tn: 106290.0000 - fn: 83.0000 - accuracy: 0.9991 - precision: 0.8699 - recall: 0.5632 - auc: 0.9014 - prc: 0.6735"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.0044 - tp: 138.0000 - fp: 17.0000 - tn: 132865.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8903 - recall: 0.5798 - auc: 0.8980 - prc: 0.6890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.0044 - tp: 164.0000 - fp: 25.0000 - tn: 159439.0000 - fn: 116.0000 - accuracy: 0.9991 - precision: 0.8677 - recall: 0.5857 - auc: 0.9025 - prc: 0.6822"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.0044 - tp: 182.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8708 - recall: 0.5759 - auc: 0.8976 - prc: 0.6778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 46.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.0044 - tp: 182.0000 - fp: 27.0000 - tn: 181933.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8708 - recall: 0.5759 - auc: 0.8976 - prc: 0.6778 - val_loss: 0.0018 - val_tp: 58.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 11.0000 - val_accuracy: 0.9996 - val_precision: 0.9206 - val_recall: 0.8406 - val_auc: 0.9636 - val_prc: 0.8943\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 56: early stopping\n"
     ]
    }
   ],
   "source": [
    "model = make_model()\n",
    "model.load_weights(initial_weights)\n",
    "baseline_history = model.fit(\n",
    "    train_features,\n",
    "    train_labels,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    epochs=EPOCHS,\n",
    "    callbacks = [early_stopping],\n",
    "    validation_data=(val_features, val_labels))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iSaDBYU9xtP6"
   },
   "source": [
    "### 查看训练历史记录\n",
    "\n",
    "在本部分，您将针对训练集和验证集生成模型的准确率和损失绘图。这些对于检查过拟合十分有用，您可以在此[教程](https://tensorflow.google.cn/tutorials/keras/overfit_and_underfit)中了解更多信息。\n",
    "\n",
    "此外，您还可以为您在上面创建的任何指标生成上述绘图。假负例包含在以下示例中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:17.021301Z",
     "iopub.status.busy": "2023-11-08T01:17:17.021014Z",
     "iopub.status.idle": "2023-11-08T01:17:17.027994Z",
     "shell.execute_reply": "2023-11-08T01:17:17.027126Z"
    },
    "id": "WTSkhT1jyGu6"
   },
   "outputs": [],
   "source": [
    "def plot_metrics(history):\n",
    "  metrics = ['loss', 'prc', 'precision', 'recall']\n",
    "  for n, metric in enumerate(metrics):\n",
    "    name = metric.replace(\"_\",\" \").capitalize()\n",
    "    plt.subplot(2,2,n+1)\n",
    "    plt.plot(history.epoch, history.history[metric], color=colors[0], label='Train')\n",
    "    plt.plot(history.epoch, history.history['val_'+metric],\n",
    "             color=colors[0], linestyle=\"--\", label='Val')\n",
    "    plt.xlabel('Epoch')\n",
    "    plt.ylabel(name)\n",
    "    if metric == 'loss':\n",
    "      plt.ylim([0, plt.ylim()[1]])\n",
    "    elif metric == 'auc':\n",
    "      plt.ylim([0.8,1])\n",
    "    else:\n",
    "      plt.ylim([0,1])\n",
    "\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:17.031522Z",
     "iopub.status.busy": "2023-11-08T01:17:17.030991Z",
     "iopub.status.idle": "2023-11-08T01:17:17.672866Z",
     "shell.execute_reply": "2023-11-08T01:17:17.672001Z"
    },
    "id": "u6LReDsqlZlk"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_metrics(baseline_history)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UCa4iWo6WDKR"
   },
   "source": [
    "注：验证曲线通常比训练曲线表现更好。这主要是由于在评估模型时，随机失活层处于非活动状态。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aJC1booryouo"
   },
   "source": [
    "### 评估指标\n",
    "\n",
    "您可以使用[混淆矩阵](https://developers.google.com/machine-learning/glossary/#confusion_matrix)来汇总实际标签与预测标签，其中 X 轴是预测标签，Y 轴是实际标签："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:17.678297Z",
     "iopub.status.busy": "2023-11-08T01:17:17.677545Z",
     "iopub.status.idle": "2023-11-08T01:17:18.235190Z",
     "shell.execute_reply": "2023-11-08T01:17:18.234327Z"
    },
    "id": "aNS796IJKrev"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 7s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "34/90 [==========>...................] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 1ms/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/28 [>.............................] - ETA: 1s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/28 [==============================] - 0s 2ms/step\n"
     ]
    }
   ],
   "source": [
    "train_predictions_baseline = model.predict(train_features, batch_size=BATCH_SIZE)\n",
    "test_predictions_baseline = model.predict(test_features, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.239881Z",
     "iopub.status.busy": "2023-11-08T01:17:18.239171Z",
     "iopub.status.idle": "2023-11-08T01:17:18.245613Z",
     "shell.execute_reply": "2023-11-08T01:17:18.244793Z"
    },
    "id": "MVWBGfADwbWI"
   },
   "outputs": [],
   "source": [
    "def plot_cm(labels, predictions, p=0.5):\n",
    "  cm = confusion_matrix(labels, predictions > p)\n",
    "  plt.figure(figsize=(5,5))\n",
    "  sns.heatmap(cm, annot=True, fmt=\"d\")\n",
    "  plt.title('Confusion matrix @{:.2f}'.format(p))\n",
    "  plt.ylabel('Actual label')\n",
    "  plt.xlabel('Predicted label')\n",
    "\n",
    "  print('Legitimate Transactions Detected (True Negatives): ', cm[0][0])\n",
    "  print('Legitimate Transactions Incorrectly Detected (False Positives): ', cm[0][1])\n",
    "  print('Fraudulent Transactions Missed (False Negatives): ', cm[1][0])\n",
    "  print('Fraudulent Transactions Detected (True Positives): ', cm[1][1])\n",
    "  print('Total Fraudulent Transactions: ', np.sum(cm[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nOTjD5Z5Wp1U"
   },
   "source": [
    "在测试数据集上评估您的模型并显示您在上面创建的指标的结果："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.249533Z",
     "iopub.status.busy": "2023-11-08T01:17:18.248817Z",
     "iopub.status.idle": "2023-11-08T01:17:18.649557Z",
     "shell.execute_reply": "2023-11-08T01:17:18.648795Z"
    },
    "id": "poh_hZngt2_9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.0030497945845127106\n",
      "tp :  84.0\n",
      "fp :  12.0\n",
      "tn :  56843.0\n",
      "fn :  23.0\n",
      "accuracy :  0.9993855357170105\n",
      "precision :  0.875\n",
      "recall :  0.7850467562675476\n",
      "auc :  0.9389954805374146\n",
      "prc :  0.8279591798782349\n",
      "\n",
      "Legitimate Transactions Detected (True Negatives):  56843\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  12\n",
      "Fraudulent Transactions Missed (False Negatives):  23\n",
      "Fraudulent Transactions Detected (True Positives):  84\n",
      "Total Fraudulent Transactions:  107\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "baseline_results = model.evaluate(test_features, test_labels,\n",
    "                                  batch_size=BATCH_SIZE, verbose=0)\n",
    "for name, value in zip(model.metrics_names, baseline_results):\n",
    "  print(name, ': ', value)\n",
    "print()\n",
    "\n",
    "plot_cm(test_labels, test_predictions_baseline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PyZtSr1v6L4t"
   },
   "source": [
    "如果模型完美地预测了所有内容，则这是一个[对角矩阵](https://en.wikipedia.org/wiki/Diagonal_matrix)，其中偏离主对角线的值（表示不正确的预测）将为零。在这种情况下，矩阵会显示您的假正例相对较少，这意味着被错误标记的合法交易相对较少。但是，您可能希望得到更少的假负例，即使这会增加假正例的数量。这种权衡可能更加可取，因为假负例允许进行欺诈交易，而假正例可能导致向客户发送电子邮件，要求他们验证自己的信用卡活动。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "P-QpQsip_F2Q"
   },
   "source": [
    "### 绘制 ROC\n",
    "\n",
    "现在绘制 [ROC](https://developers.google.com/machine-learning/glossary#ROC)。此绘图非常有用，因为它一目了然地显示了模型只需通过调整输出阈值就能达到的性能范围。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.653284Z",
     "iopub.status.busy": "2023-11-08T01:17:18.652996Z",
     "iopub.status.idle": "2023-11-08T01:17:18.658273Z",
     "shell.execute_reply": "2023-11-08T01:17:18.657586Z"
    },
    "id": "lhaxsLSvANF9"
   },
   "outputs": [],
   "source": [
    "def plot_roc(name, labels, predictions, **kwargs):\n",
    "  fp, tp, _ = sklearn.metrics.roc_curve(labels, predictions)\n",
    "\n",
    "  plt.plot(100*fp, 100*tp, label=name, linewidth=2, **kwargs)\n",
    "  plt.xlabel('False positives [%]')\n",
    "  plt.ylabel('True positives [%]')\n",
    "  plt.xlim([-0.5,20])\n",
    "  plt.ylim([80,100.5])\n",
    "  plt.grid(True)\n",
    "  ax = plt.gca()\n",
    "  ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.661725Z",
     "iopub.status.busy": "2023-11-08T01:17:18.661085Z",
     "iopub.status.idle": "2023-11-08T01:17:18.948757Z",
     "shell.execute_reply": "2023-11-08T01:17:18.947997Z"
    },
    "id": "DfHHspttKJE0"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Y5twGRLfNwmO"
   },
   "source": [
    "### 绘制 AUPRC\n",
    "\n",
    "现在绘制 [AUPRC](https://developers.google.com/machine-learning/glossary?hl=en#PR_AUC)。内插精确率-召回率曲线的下方面积，通过为分类阈值的不同值绘制（召回率、精确率）点获得。根据计算方式，PR AUC 可能相当于模型的平均精确率。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.952731Z",
     "iopub.status.busy": "2023-11-08T01:17:18.952444Z",
     "iopub.status.idle": "2023-11-08T01:17:18.957303Z",
     "shell.execute_reply": "2023-11-08T01:17:18.956539Z"
    },
    "id": "XV6JSlFGEqGI"
   },
   "outputs": [],
   "source": [
    "def plot_prc(name, labels, predictions, **kwargs):\n",
    "    precision, recall, _ = sklearn.metrics.precision_recall_curve(labels, predictions)\n",
    "\n",
    "    plt.plot(precision, recall, label=name, linewidth=2, **kwargs)\n",
    "    plt.xlabel('Precision')\n",
    "    plt.ylabel('Recall')\n",
    "    plt.grid(True)\n",
    "    ax = plt.gca()\n",
    "    ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:18.960914Z",
     "iopub.status.busy": "2023-11-08T01:17:18.960328Z",
     "iopub.status.idle": "2023-11-08T01:17:19.245348Z",
     "shell.execute_reply": "2023-11-08T01:17:19.244697Z"
    },
    "id": "FdQs_PcqEsiL"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xijq9uP6g+/W/Nh/WwplDdPuFg4NaR1Vd01S9bTmlemL1br8+Z2RmvGYMTwtUWQAAAAgiwhFCKi7KLKvZ6LGa3Z7ClnscdbbIZiv05ZXV6vdrOl45ry3//dE5GpEZH4iyAAAAEEQ8XIGQio8y69+3TtHFZ6a7z6WEYKPXYelxAfus//d5nt7fVaj3dxVq86ESOZyuji8CAABAyDFyhJA7s3e85ozqrVU7CiRJKbHBD0ffGpupYRmxKqqs9+v636zaqR155ZKkZz7Yr2c+2O9+LxTTBAEAAOA7whHCwrGKpk1tU0MQjgwGg87s7f9UuH9tPuwOR6fakdd5q+wBAAAgcAhHCAuFJ5bRlqTUuOCHo9O15BtnalSfeFXVOSRJu49WaMUX+ZKkt3cc1cd7inTO4F6hLBEAAAAdIBwhLBRW1Klfsk0VtQ1KjbW6z9/xylYdLKrq8PrrJmfr2+P6dGaJ7UqKjtRN0wa4X6/4PN8djiTp/V2FhCMAAIAwRzhCWKiotat3fJTu+c4wpcc1haPdRyv1dX7r09Waaz7yFA5mDk9TUnSkiqsan2F6/uMDmjIwWReewTLfAAAA4YrV6hAWvj22jxJsZo3KSlC8zew+bzR498dgaOfDQyAywqibm40kSdKfTmwyCwAAgPDEyBHCwkVnpuuiZst5n7Ti9mkhqCYwLj0rQ0+t3auK2sYNZjcdKtGdr2zV4LRY3XruQBmNYZboAAAAejhGjtDlVdU1qLS6Xi5XeO0n1DfZpmeuHedx7o1teXr07V1as7MwRFUBAACgLYQjdHmrvizQ6F+s1vDFb+tfmw+HuhwPQ9JjW12aPIJRIwAAgLDDtDp0eXmlNZKkGrtDO/LK1CcxyuN9q9mk0VkJHue+zi9XWY29w89Oj7Mqu1e0x7lP9h/3qq5h6bHqFWPRxz+7QPllNbrjn1u17XDjnkf7iyoVtd/U5rUT+yfJ0OxBqkPF1dpbJn16oFgREW3/YxtnNWt47ziPc58fLlV1vaPDevsm2dQ7oenvrq7Boa05pR1e1yvGokGpMR22AwAACHeEI3R5eWVNG8j+Zd1B/WXdQY/3B6RE670fn+dx7lf/26kPdh/r8LPnT83WA3PO9Dh39bOfyJsZfH+Zf7bOH5qqyAij+iVHu4ORJD3036/bvfb1H06R8UQ4GpgSrX9+lqvnv4rQH77a1O515wzqpX/cNNHj3E9e+1y7jlZ0WO/PZw/TLdMHul+XVtv1nT9/0uF1krRs3mjNHZPpVVsAAIBwRThClxdr7RrdODvZpoPHq71q+62n1ruPE21mXTIivJcA/7qgXHNFOAIAAF1b1/itEmjH7RcOVnJ0pEqqW58mlxwd2eLcpWdl6IyMuFZaexrfL7HFuR+cO9CrkaO+STaP13FWcxst21dSbVe/JJsu7O3UwIEDZDS2PR0vO9nW4tyV4/uoqLK+w/uM6pPg8doWadIPzh3YeuMTIowGzRyepvgo/74bAABAOCEcocuLsUTo+x38En+qq87O8vt+P7t4mF/X/f7qMVq+KVc1Xjz/I0lvbc9zbyK7dNVuSUatyTvYZvvoSJN+fukZLc7fdMp+S96KtZp1zyX+fVcAAICuiHAEBEl2r2ifgtW6vUXucOSNqnqH/r35sK6Z2M+f8gAAAHo8whEQphbNHqY/f7hftXanXC6XSktLlZCQ4LGKnSRV1Nq171iVJGlLTqnmPrlO2ck2PTR3hGL9nMoHAADQExGOgDB1wbA0XTCscSEGu92ulStXavbsiTKbPQPP6q+O6ua/Na1ity23VNtySzVpQLK+M6Fvp9T2/q5CvbjuoD7YfUzZyTYNSGl9Ke/0eKseufwsj3NPrN6tL4+Utdq+uRlnpOm7Ez3rv/HFjWrrcS+T0aBvj83UxSMyvPoOAAAApyIcAV3cuH6JOrN3nHbklXucr6xr6LR77jhS5l4K/eDx6jZX4RuYEt3i3PbcUq+WUe/XyuIS7+0qbHcxjA93H9POh9JbjK4BAAB4wxjqAgCcnqToSK24fZoO/upSzTqzacnvlz7N6bR7Th3USzGW8Pv/VhJsTCMEAAD+C7/fbgD4LTOhabTF5XLpzW1HOuU+VrNJH//s/A6XNDcaW47g/PG7Y9Tg6HgtdIu55f93s+W+mS3O7Syo0NXPNm5We3Z2EqNGAADAb4QjoBs5f1iKXlh3QFLjdLc7XtnWafe6dGSGnvzuWJ+vO51FIhJb2bNq8sBkfbLoQm08WKyUWIvfnw0AAEA4ArqRRFvL8NBZ9hVW6tDxqjbft5pNSouzBqWW9Hir5ozqHZR7AQCA7otwBHQjIzLjtfyWSfo6v7zjxn7YdbRC//wsV1LjdLZzH13bbvtrJ/XVL+ee1W6bQDhWUaeyGs89ofok2mQ1mzr93gAAoPsgHAHdzMQByZo4ILlTPvu9nUfd4cgb6/ce75Q6TvXsR/v15w/3e5zrFROp/90xnal2AADAa4QjAF47b0iqfnrxUO0qqGizzfHKen28t0iSdKi4WmMfWu3XvVJiLFr2ndE6IyPOr+uLKut16HgV4QgAAHiNcATAa0ajQT88b1C7bd7fWegORw6nS8VV9e22b0txVb3e2HbEq3A0sk+8rhzXR5L01vY81TU4ZTIaNMzPYAUAAHomwhGAgJo8MFmXjszQl0fK/Lq+uLJeFSc2sF2946j2HK10vxdrjdCPLhikQamxHtdcNrK3LhvZWyVV9Xpt82FJ0pm948JyLyYAABC++M0BQEBZzSa/lvg+aeGr2/T6lsb9mfYXVWl/keeKePUNTv3p2nGtXrvxYLH7eEJ2kt81AACAnqnlLosAEEIXDEtVZETb/2qKj2p7nySPcNSfcAQAAHzDyBGAsHLZyN6acUaaauod7nNPf7hPz3zQuBrd2e2MCMVYzMpMiNKR0hqdnZ2k4qp6PbLya6/u+9NZQ5XabF+mDfuO699bDnd4XaLNrHsvHe5x7sV1B/RlXsfLqU/sn6Qrx2d5nFv0+heyO5zu1zGWCP3f1P7qm2zr8PMAAMDpIRwBCDtWs8ljj6KvmgWNeodTH+4+1up1Y/omaEzfBJVU1+uLI2U6VlGnf23uOOBI0tnZicqIj3K/fm9noVfXZiZEtQhHG/Yf19s7jnZ4rdlkbBGO3th6RDV2h8e5vNIa/fm68R1+HgAAOD2EIwBhzel0acuhEvfrRa9/0Sn3+dm/O+dzA8EWyWa2AAAEA+EIQFgzGKQIk1GSo8O2nen8oSm6c8aQFucjTAaV19o9zv34oqEdLnkuNa6+d+q1r3x/kuSS/rrhoHthinHZiS3ancogKdba9vNYAACgY4QjAGHNYDDonzdP0rtfH1WD0xXUe6/bW6TNJ0at3t91TO/van06X2e7/40duv+NHR22m9A/Sf+4caIMQagJAIDuiHAEIOwN7x2n4b2Dv6FrVV2DOxx1BZ8dKFZRZZ1SovlXOwAA/uC/oADQhpunDVBJVb2KquqDet+iijp9ld+4CEXvhCgNSo1Rg8Op1sbNGhxObTzYFOCufvYTmQxSZaVJv9vzsVySvB1wMxoaR+pOcrlcXl9rMnqOVzmdrlbrPVV0ZITunjVEFwxLc58rra736r62SM+FOxocTpXXNnhVb3yU2aPmWrtD1fUdT900GQyKt3lOXyyvtavB0XHBlgijok/ZmLjYy74VY4nwWOK+vsGpyjrvvmuizezxc62qa1BdQ9OKiHa73eufMwB0d4QjAGhDerxVT8wbHfT7Hquo03s7j+rjvcf1nbOzNHVQL33rqXXaklPa4bWHjlefODKosLa63bbh4sn393mEo0t+95Hyy2o7vO5X3zpL35nQ1/36QFGVZv72Q6/uuf6eC9Q7oWl1wn98cki/XNHxsu+DUmP07sJzPc4teHlrmysoNvd/U/tr8RzPlQ3HPrTaq3pfnH+2zhua6n79yf7juu6Fz7y69sDS2R6vf7t6t577+IDHuXizSWOn1qhfCs+tAejZCEcAEGZSYi2ad3ZfzTu7b8eNTxFpMshqNslut8tsNsvlcqmizrvFLGyRJkU0G02xO5yqsTvbuaJJnNXzPyc1dofsXoymSNLmQyVa+Oo29+vS6vYXnzhp+aZcfdZs49/yGu+uQ0tldoO+OFKufinBn74KAOGEcAQAXcD47CQl2iI7bDdnVG9dOiJVK1eu1OzZs9TgMmrBy1u8usei2cM0KDXW/XrTwWL9ae2+Dq+zmk168pqxHuf+su6APt5T1OY1+4uqdKCoyv365Mp8vtiaU6qtHYymje2b0Orfm6XZFDVJykqy6cJhqS3anSojwdri3OisBJmNHS+DMSQtpsU5b+4pScnRFo/XSdGRXl97qsFpMe5r1+0rUu2JADyyT7xfnwcA3QnhCAC6gJ/PPsPrtnZ70whKVKRJz99wtl/3HJ+dpOdvSPLr2vlT+2v+1P5tvv/h7mOa/+JGOTr5YZfBqbEakdlyNGTlF/ktzp03NMV9HBlh1PnDUpUa2zIMnWrhzJZLvHvL35/NiMx4v689OSpZVm3XmIfekSSlRbmUEd/xdwWA7o5wBAAIuulDUrTl/pk6XlkX0M91Sbrw8Q/cr5dvytXyTf591qisBL1529TAFBaG1u0rci/EMCyBFRkAQCIcAQBCJD7KrPiowC8A0CcxSodLak77c3YVlAegmvDVfBGJM+IJRwAgEY4AAN3M6z+cog37jvs1Ze/tHQV6e8dRSVKt3amXPj2kayb2C3SJYaFvsk2DU2OUU1ytgXEN2nSoRGv3HO/wuuToSN0yfaDHuVc35mpfUWWH147vl6SZw9M8zv3qfzvlzcLvV47L0qDUpue2DhRV6ZWNOR1eJ0k/mzVMxmbPhX24+5jS4qwamh7bzlUAeiLCEQCgW0mNteqbozP9ujbCZHSHI0n68kj3HT364XmD9MPzBqmwrEob1r6rL46U65kP9nd43cCU6BbhaMUX+frAi+XM66c6W4SjZz7cJ5cXOXbSgGSPcHS4pNqreqXGcHRSbnG1Ptx9TO98dVQf/vR8r64H0HMQjgAAOOHSszJ096vbVe9oXMHtn5/l6NVNuR1eZzIY9O1xmXrk8rM8NlztCrxZBbG7qLU7NO+ZDRrTL9Gr0SoAPQ/hCACAE0xGg2YOT9OKZqvZeTM9zyGX/vlZrh765ghFmLpWODrp4jPTNCorscN2VrOpxblFs4fph+cNbKW1p/RWVsR75eZJXtV36hS4kZkJWn6Ld9eezKtbc0qVV1arvM/zdeW4Pl5dC6BnIRwBANDMD84dqPJau8q82FT2eGW9jpQ2Lf4w78+f+H3fs7OT9NNZQz2ejQmmjHir+vby7xmcYen+bx47cUCyX9fF28w+X/vJ/qZnqib5eV8A3RvhCACAZs7qE6+/3zjRq7Yf7Tmm7z3/mfv15kMlft9386ESzT4rXSP7JPj9GWjfhubhaCDhCEBLhCMAAPw0MjNBwzPi9FV+YBZueP7jA+oVY+mwXYTJoMvO6q2z+sQH5L49Qa3doW05pZKkvkk2ZSZEhbYgAGGJcAQAgJ/ibWatvGOaX8uGS1JlbYNG/eId9+s3t+V5fe2/Nx/Rpvtm+HXfnmjLoRL3Qhs5xdXqv2iF/nj1WF06MsPdZvOhEl3x9Hr366Fpsfr7jROVEttxYAXQPRCOAAA4TSY/nxOKijSpf69oHSiq8vnaoso6/fdz78NUWxwNDm0tMkhfFMgU0XKxhVMlRUdqYv9kv79zqOSX1Xq8bmv58ObndxZUaOPBYs0+K6P1xgC6HcIRAAAhEhlh1P/umKav8svl8mKzn4/2FGnZu3vcrxe8vDVAlZj04p7PvW597+wzdPP0AQG6d3Bccla61u0t0r5mQTTBZvZoE20xaVRWgnYVlKvW3jjKNCQtRgB6DsIRAAAhZDWbNLZvx0ton9Q8HIXKzoIKHS6pDshn2SIjlBTd+Xst2SIj9MS80e22GZYep3//YLLG/GK1auVUr5hIDUwhHAE9CeEIAIAuYly/JL1000R9HaAFICTJ6XTqq6++0vDhw2U0Gtts98a2I/rySON9/73lsP695XDAarj9wsFaOHNIwD7vdHyVX66KugZJjcuMd7VNfQGcHsIRAABdyNRBvTR1UK+AfZ7dbtfK0h2aPaWfzGZzm+2+OFLmDkeBtn5vUdiEI/ZCAno2whEAAOjQ3RcNVYwlwqvNcb1x8HiVO2x9frhM43/5riQpOTpSj145MmT7PX26v9h9PKl/kvv45U9zVFnX8XefOqiXzuzdtMR6aXW9Xt2U69W9vzOhr+KsTQH1yyNlWr+vqMPr4qPMmnd2X49zq77MV05xx1Mfz+wd3yJsP/fRfjnbeAbO4XBqZ55BeR8f1OyRvdUvOdr93pHSGq1oZZEQo8GgaYNTNDTdv02GgWAiHAEAgA5lJdn08OVnBezznnx/rzsc1TucKqqsk9S4Ct+rm3JDFo4255Ro6qBkOZwuDUptet7oqbV7dbikpsPrfzl3hEc4Kq6q1yMrd3p170tGZHiEo00Hi726tn+v6Bbh6NVNh/XezsIOr71+cr8W4ehX/9uphnaXpzfpzUO7NSQ9ziMcHSqqarPeWMsebbp/hixerIgIhBLhCAAABN3cMZn6YNcx5ZU1Bo7SarsqTzzrs27vcd30100Bvd/kgcn6v6nZHT5D1CcxStGREfrdd8bwvFEAVdQ1+L0fGBBMhCMAABB0mQlRevUHk92vF7y8Rf/9PF+SdKCoyq+9n9rz7tdHNW1wLw1Ja39q10s3TdKh41WKivQc4Xho7gjV1js6vE/zUSNJSo2z6k/XjPWqxuQYz1X7zhuaqj/FWTu8zmZp+evcD88bqCvH9enw2r7Jthbn/vjdMW3uA9XgcGjLli0aO3aszsr0/K5D0mM9vqvTJf3on1vkdEn9km2yRfJrJ8IfvRQAAITcuUNS9PaOAtkdnTe68MpnuS0CSFs+2tPxsz59EqM0Z2RvGdvZEDfGEqFL/NxENrtXtLJ7RXfcsBXjs5M6btSGi0e0Xa/dbpfzkEsXn5nWYgGPXjEWj+96sKhKJweLhnYQSoFwQTgCAAAhd+X4LF06MkPVXozOeMvucGrKr95zj4K8sO5AwD77JKfLpcvHdDxC0xPtO1bpPh6WERfCSgDvEY4AAEBYsEVGBHTqlcPpUp/EKOUWd7yQgr+25ZRqWHqchqXH8ozSKS48I01b75+pnQUVSo/veHogEA4IRwAAoFsyGQ3674Jp2pJTEtDFAB57Z5d2FlRIkv664ZD+uuGQlnzjTF0/JTtg9+guEqMjNXlgslZ9ma8rn17fYfu4KLPe+/F5HuceePNLrfgiv8NrLzozXY8EcEVF9EyEIwAA0G3F28w6f1hqQD/z1U257nB00tf55ao6sdqer0xGg6zm7r3EdV2DU0WV9R22a20J8Yq6Bq+uraz17+8faI5wBAAA4INfzh2hMX0TterLfG0/XCZJemVjrl7Z6N1mr625ekKWln5rZKBKDDtRZpOykqI6bNd8n6eTkqMjvbrW28U2gPYQjgAAAHyQGmfVrecNVH5ZjTscna63tuV163B00ZnpuujMdL+uvffS4br30uEBrghoHeEIAADADzdPG6DSaruKqzqe8tWaqvoGbc0pldS4RxCA0CMcAQAA+CEryabfXz3G7+vf3lGg7/99syTp7NPYl6inczhdWvjqNvVLsml03wRdMCwt1CWhCyMcAQAAhMCmg8Xu4y2HSvST17a32s5qNumaSX01LJ29glqTV1qjN7flSZJmDk8jHOG0EI4AAABCYEdeuft406ESbTpU0mbbz4+U6c3bpgajrC5nf1GV+3hASnQIK0F3QDgCAAAIgbOzk7R+33Gv2h4rr9VLnx5qt41BBk3on6hBqT3r+aX9xyrdxwN7xYSwEnQHhCMAAIAQuGvmEH1nQlab+yN9uLtIv/jvV5KkvLJa3fufLzv8TFukSet+doESo3vOstb7jzWNHPVn5AiniXAEAAAQIhnxbe/fU+7HpqbV9Q5tzS1RWpzVq/ZJ0ZHt1tAVHGg+ra4X4Qinh3AEAAAQhsb2TdQbt03VnqMV7bZzuaR7Xv9cTlfj6/97cZNP9/nNFSN11fgsf8sMuZPT6uKjzErqQSNm6ByEIwAAgDA1OitBo7MS2m3jdLr0wFs7VGN3+HWPrTmlXTYcVdc3KK+sVpLUv1e0DAZDiCtCV0c4AgAA6MKMRoP+Mv9srfwiXw0nh486sONImbYfLpMkLd+Yo39vOdzhNSaDQd8Yla4p5tMqN6CaT6kzmzyD0cov8vXOjgIt/dZIRUWagl0auijCEQAAQBc3aUCyJg1I9rr94+/scocjp0uqb3B6dd3yTUc0YaJfJXaKosp69/HsszLcx18eKdPxqnq9sS1Pl47srZnD2fsI3iEcAQAA9DBXT+irL4+U6Wh5XYdtXZK+zm/ak+mpr0x65ejGVqewZSXa9OA3hivWGpzhpbF9EzRpQJI+P1ymaYNT3Of/tfmwXtmYI6nxWSTAW4QjAACAHqZ3QpT+Mn+CV21Lq+s1+her3a/3VRi0r6L1DWs/O1Cs0X0T9L1J/QJSZ0dirWa9csvkFuf3F1Wp1t44GtafFezgA8IRAAAA2hRnNeui4Wl656ujXrV/Z0eBDhdXt/6mQTpnUC+PUZ7OcKCocQW7WEuEesWwgh28RzgCAABAm4xGg/583XjZHU7V19u1atUqXXzxxTKbm6ar3bV8m1Z8kS9J+mhPkT7aU9Tm5z330QFtWHSBUmO924vJV3UNDh0uqZHUuCksK9jBF8ZQF/Dkk08qOztbVqtVEydO1GeffdZu+2XLlmno0KGKiopSVlaW7rrrLtXW1gapWgAAgJ7JbDIqMsKoCKMUGWH0+DMiM97rz3E4XXr7ywL974t895+v8so7vtBLOcer5TqxaJ8lwqj3dxWqqLLjZ6sAKcQjR8uXL9fChQv19NNPa+LEiVq2bJlmzZqlXbt2KTU1tUX7l19+Wffcc49eeOEFTZkyRbt379YNN9wgg8GgJ554IgTfAAAAAD84d4AuGJaqshp7m21u/OtGVdQ2SJLuf3NHi/df+8FknZ2ddNq17G+2vPfGgyWa/5eNev768brwDFasQ8dCGo6eeOIJ3XzzzZo/f74k6emnn9aKFSv0wgsv6J577mnRfv369Zo6daq++93vSpKys7N19dVX69NPPw1q3QAAAGhiMBg0ND223TYZ8VZV1Fa2+f723FL1SYySNcKkxGj/nxOKtfLUCPwXst5TX1+vzZs3a9GiRe5zRqNRM2bM0IYNG1q9ZsqUKfrHP/6hzz77TBMmTND+/fu1cuVKfe973wtW2QAAAPDDCzecrdVfHZXd0bSn0n+25rmXCf/liq/1yxVfS5K+f+4ALbrkDL/uM2VgLz197VjtLKhwn+vfK1qfHShWaXW9+veKVnavaJlNIX+6BGEoZOGoqKhIDodDaWmeQ5xpaWnauXNnq9d897vfVVFRkc455xy5XC41NDToBz/4gX7+85+3eZ+6ujrV1TXNMy0vb/wH0G63y25ve+i3s528dyhrQNdBf4Ev6C/wBf0Fvjid/pIWY9a1E/p4nPvicKnHHkonvf91oe6eMci/IiVdOLSXLhzay+Pcb1bt1KodjSvuvXvnOeqXbPP78+GdcPr3i7c1dKlxx7Vr1+qRRx7RU089pYkTJ2rv3r2644479NBDD+n+++9v9ZqlS5dqyZIlLc6/8847stlC/w/F6tWrO24EnEB/gS/oL/AF/QW+CFR/GW2SilKNqmmQqh3S7rLG0Zx9xyo0/hdvt3pNVoxL1w12ymLy7V5fHDBJMshocOnzT9ZqB4vYBU04/PulurqN5eVPYXC5Tq7nEVz19fWy2Wz617/+pblz57rPX3/99SotLdWbb77Z4ppp06Zp0qRJevTRR93n/vGPf+iWW25RZWWljMaWw6OtjRxlZWWpqKhIcXFxgf1SPrDb7Vq9erVmzpzpsRQm0Br6C3xBf4Ev6C/wRWf2l605pbrq2fZXLT7pue+N0blDvN8ryeVyafQv31N1vUPZyTatvvMcf8uED8Lp3y/l5eXq1auXysrK2s0AIRs5ioyM1Lhx47RmzRp3OHI6nVqzZo0WLFjQ6jXV1dUtApDJ1Ph/G7SV8SwWiywWS4vzZrM55D+kcKoDXQP9Bb6gv8AX9Bf4ojP6y6h+SfrGqN7adLC41fePV9WrrqHxeaVnPjqo17bkud+LMBl1xbg+On9oy9WOJeloea2q6x2SGp8/oq8HVzj8+8Xb+4d0Wt3ChQt1/fXXa/z48ZowYYKWLVumqqoq9+p11113nTIzM7V06VJJ0pw5c/TEE09ozJgx7ml1999/v+bMmeMOSQAAAOh6LBEm/f7qMW2+P++ZDfr0QGNw2niwpMX7H+0+ps8fnNXqtfuPNS3vnd0r+jQrRXcW0nA0b948HTt2TIsXL1ZBQYFGjx6tVatWuRdpyMnJ8Rgpuu+++2QwGHTffffpyJEjSklJ0Zw5c/Twww+H6isAAAAgCC48I1WfHSxWWw+EWMxt/x/lB483haP+hCO0I+QLMixYsKDNaXRr1671eB0REaEHHnhADzzwQBAqAwAAQLi4ZfpAfWdCX9WemB4nSaU1dl302w8lSQNT2g49B4sIR/BOyMMRAAAA4I04q1lx1qZnR3JLmlYgK6qsV2F5rVLjrC2uO9AsHGUnE47QNna/AgAAQJe0r7Ap9OwtrNS037yvfccqW7Q7Oa0u0mRU74SooNWHroeRIwAAAHRJ1kjP54zqGpzamV+hzFMCUJzVrFhrhNLirDIZDco5Xq2ymsZNQa1mowamxMhoZOMjEI4AAADQRV12Voaq6hq06PUv3Odue3lLm+0TbA4dLa/Vo+/s0v/b3rQU+JXj+ujRK0d1aq3oGphWBwAAgC7JaDTo6gl9NeOM1vc3OlVucY02trKP0uaclkuDo2di5AgAAABd2l0zh8hoMKiitqHV9/cUVqqosk6S9OtVOzUgJUaXj8nUf7YekST1SbQFrVaEN8IRAAAAurQze8frz9eNb/P9H760WSu/KJDUOHqUW1yjJ787xh2OspMJR2jEtDoAAAB0a1eM66O0OIvHuec+OuA+rm62dxJ6NsIRAAAAurULhqXp05/P8Bgh2ppb6j7+1+bDyiutCUFlCDdMqwMAAECPMKF/kg4er271vf9sPaJeMZH6Kq9cB4qqNCIzXnfMGCxLhKnV9uieCEcAAADoEX797ZG69bxBqmtw6O7XtuvLI+Xu9x59e5dH2w/3FCkryaarJ/QNdpkIIabVAQAAoEcwGAzq3ytaw9LjdMmIjA7bsy9sz8PIEQAAAHqc284fpEtHZmjzwRLZHU5J0vMfH9Cewkp3m75J0aEqDyFCOAIAAECPlJ0crezkpgD0/McHPN7vxxLfPQ7T6gAAANDjOZ0u5RR7Ltbwxol9kNBzEI4AAADQ49U7nKprcHqc+/snh0JUDUKFcAQAAIAez2o26UcXDPQ4lxQdGaJqECqEIwAAAEDStMGpHq955qjnIRwBAAAAkg4dr/J4zWp1PQ/hCAAAAJA0bXCK5p3dx/2akaOeh3AEAAAASEqPtyrWYna/7pdEOOppCEcAAADACYeaLefdl5GjHodNYAEAAIATduaXS5KMBumZD/bLaGh6LyvJpvlT+8vU/CS6FcIRAAAAejy7w6nVXxWosLxOkuR0tb7PUVJ0pL41tk+L8+gemFYHAACAHi/CaNCyd/eozuFst119Q/vvo2sjHAEAAKDHMxgMevAbZ7pfX3pWut5aMFVvLZiqOaN6u8/zHFL3xrQ6AAAAQFJeaa37eGy/JI3skyBJqrM73Of7soJdt0Y4AgAAACTlNNsE9q3tedp8qFiS1OB0amL/JFXXN+jhFV/JYDBoQK8Y3TFjsMwmJmJ1J4QjAAAAQNLRE4sxSNL23FJtz23Z5osj5e7jwWkx+ubozGCUhiAh6gIAAACSzh2a4tMy3UYDS3p3N4wcAQAAAJJmn5Wh6UNSVFFrb7PNb1bt0n+2HpEk9UmMClZpCBLCEQAAAHBCjCVCMZamX5G/PFKmbbml6ptk08g+8Squqne/V1hRp40HG59LSrSZNTAlRgZGk7o0whEAAADQhrW7CvXYO7slSU9fO06HS6rd733/75s92v5y7ghdO6lfUOtDYPHMEQAAANCGQ8ebwlDfJJtskW2PLXx+uDQIFaEzMXIEAAAAtCGnuCkcZSVF6fdXj9HrWw6rrsEpSdp/rFLvfl0oScqI5xmkro5wBAAAALQh90Q4SoqOVKzVrFirWT++aKj7/b+uP+gORyzQ0PUxrQ4AAABoRV2DQ/nltZKkrCRbq22aP4PUJ7H1Nug6CEcAAABAKw6X1Mjlajzu20Y4yi2ucR8zctT1EY4AAACAVjR/3qhfWyNHpY1tTEaDMuKtQakLnYdwBAAAALQit9hzpbrWHC5pHDnKiLcqwsSv1l0dP0EAAACgFTnHm69U1zIcVdTaVVptl8SUuu6CcAQAAAC0IsFm1uDUGFkijOqb3DIcHSlt/rwRizF0ByzlDQAAALRiwQWDteCCwXKdXJXhFIdZjKHbIRwBAAAA7TAYDK2eZxnv7odpdQAAAIAfTi7GIDFy1F0QjgAAAAA/EI66H6bVAQAAAKd4c9sRPfX+PvVLtummaQM0oX9SizbN9zhKj2OPo+6AkSMAAADgFHuOVmrX0Qq989VRVdbZW22TW8weR90NI0cAAADAKQ4er3IfbzlUqrzSWo/3Lx6RrrIa9jjqbghHAAAAwClyi5tWovvj+3tbvD8sPdZ9nMVKdd0G438AAADAKfoktR942AC2e2LkCAAAADjFr789UpeelaHqeker7x+rqHMfM62u+yAcAQAAAKeIsURo9lkZbb7/0H+/ch8TjroPwhEAAADgpZKqeq3aUaDtuSXucx1NwUPXQTgCAAAAvLSzoEKLXv/C/TrCaFBarCWEFSGQCEcAAACAl5qvYidJLkkXPP6Bx7mH5o7QuUNSglgVAoVwBAAAAHiptKbe47XD6VLOKYGppr4hmCUhgFjKGwAAAPDSJSMyPPY4ai7RZlZydKQiI/gVu6ti5AgAAADwUlaSTStun6Z7/v253t91TMVVdXK6JJPRoI33zlCEiWDUlfHTAwAAAHxgMhr06JWjtOm+GYqxNI419E6wEoy6AX6CAAAAgB/Kauwqr218vsjlkn67epfW7S1Sg8MZ4srgL6bVAQAAAH44UlLjPj5cUqPfrdkraa9MRoOWfONM9YqJbHFNUrRFZ2cnymAwBLFSeItwBAAAAPghJdai6EiTquodHucdTpfue+PLNq97YM5wzZ/av7PLgx+YVgcAAAD4ISXWolV3Ttcfrh7jfvaoPaOzEnTHhYOVYDMHoTr4g5EjAAAAwE9ZSTalxFr0o39ulST1SYzS9yb1a7WtyWjQtZP6yWo2BbNE+IBwBAAAAJyGw82ePRrbN1HfP3dgCKvB6WBaHQAAAHAackuq3cdZSVEhrASni5EjAAAA4DTkFjeFo75Jtlbb7CqokCXCqPR4K9PqwhjhCAAAADgNzcNRVmLr4ehn//5c23JLZTRIOx+6RJERTOAKR/xUAAAAgNOQ0zwctTFylF/W+FxScoyFYBTG+MkAAAAApyG3uDH4mIwGZcRbW7xf3+BUYUWdJKl3As8khTPCEQAAAOAnl8vlnlaXmRClCFPLX6+PltfK5dKJNi3DE8IH4QgAAADwU1mNXRV1DZLaXqkur7Rpqe+MeEaOwhnhCAAAAPDTySl1Utsr1eWVNbVhWl14IxwBAAAAfmq+GEOfNlaqyyutdR/3buWZJIQPwhEAAADgJ88NYNsKR4wcdRWEIwAAAMBPOV5sAEs46joIRwAAAICfPDeAbT34nFzGO9JkVHJ0ZFDqgn8iQl0AAAAA0FWdDEfRkSYltRF8/t+Cc3S8ql5FlXUyGg3BLA8+IhwBAAAAfnA4XTpyYspcVpJNBkPrwcdoNCgl1qKUWEswy4MfmFYHAAAA+KGgvFZ2R+Purm0txoCuhXAEAAAA+MHzeSPCUXfAtDoAAADAD7keK9W1vhjDR3uOae2uY8qIt+qi4enqm0yICmeEIwAAAMAPHiNHbUyrW7/vuJ7/+IAkaUhaLOEozDGtDgAAAPCDN3scHSlp2uOoTxtLfSN8EI4AAAAAPxw83vHI0eGSpjZsABv+CEcAAACAH06OHKXHWWU1m1ptc/jEyFFKrKXNNggfhCMAAADAR+W1dhVX1UuS+rXxHFGt3aHCijpJTKnrKghHAAAAgI9ymk2paysc5ZU2f96IhRi6AsIRAAAA4KNDzcLRttxS3f3adm3Yd9yjzWEWY+hyCEcAAACAj/LLmoLP7qOV+tfmw/rRP7d4tCEcdT2EIwAAAMBHE/onyRJx6q/SBo9XzVeqY1pd10A4AgAAAHw0sk+Cttw/U/+7Y5r73KnPHg1Ji9XFZ6ZrRGZcm/sgIbxEhLoAAAAAoCuKtnj+Kn1qOJo7JlNzx2QGsyScJkaOAAAAAD81X5ihX1J0CCtBIBCOAAAAAD8dOl7lPs7uxdS5ro5wBAAAAPjpUHHTyFHz54ocTpdcLlcoSsJpIBwBAAAAfvLcDLZpWt36fUUadv8qXfD4Wi3fmBOK0uAHwhEAAADgp0PFjdPqYq0RSrSZ3ecPl9SorsGp/ceqZHcwgtRVEI4AAAAAP9Q3OHXkxEav/ZJtMhia9jny3OOIDWC7CpbyBgAAAPxwpLRGzhODQqXVdj341g73ex/uPuY+fnNbnuKjzOrfK1qREUbZIvkVPFzxkwEAAAD8kFda4z4+XFKjF9cfbLXdf7Ye0X+2HpEkzZ+arQfmnBmM8uAHptUBAAAAfhiQEq1YK2MN3Qk/TQAAAMAPGfFR+vhnF+hAUVWL93YWlOvVjbnaklMqSUqOjtRZfeI1KDVGkvTsh/u1dnehMhOi9KMLBisriT2SwgHhCAAAAPBTfJRZo7MSWpwfnZWg/snRmvfnTyRJ3xjd22M63fbDpVq397gk6dbzBgWlVnSMaXUAAABAJ8gtaXomqU+i58hQ8+eVMuKtQasJ7SMcAQAAAJ2g+XLeWacs533kRDjqFWOR1WwKal1oG9PqAAAAgE6QW9w0OvTjV7cr2rJDt0wfoGsn9VNhRZ0kKZM9kMIKI0cAAABAJ6iss7uPK+oaVFBeq2c/2q+Cslq5TuyPlJnAlLpwwsgRAAAA0AluPGeA8kprVVpT7x5FKqmu1x2vbHW3yUxg5CicMHIEAAAAdIIJ/ZP0/350jt667Rz3uVq7U1tzS92vexOOwgrhCAAAAOhECTazzhnUq9X3GDkKL0yrAwAAADqRwWDQP26aqLJqu1767JB+s2qX+z1GjsILI0cAAABAEMTbzCqpqne/PndIirKSbO1cgWAjHAEAAABBcrjZxrC/nDtC8VHmEFaDUxGOAAAAgCA5GY5MRoMy4lnGO9wQjgAAAIAgOVxSLUlKj7MqwsSv4uGGnwgAAAAQBJV1DSqpbtwYtjejRmGJcAQAAAAEwZFmzxttPFSi5z7aH8Jq0BrCEQAAABAEJ6fUnZQcExmiStAW9jkCAAAAgqD5SnWStPFgiY5XNi3tHRVp0jUT+wW7LDRDOAIAAACC4NSRo5c/zfF43SsmknAUYkyrAwAAAILg1JEjhB9GjgAAAIAgOBmODJKWfWe0TEaDx/uRJ5b2fmrtXkVHRqhvsk3nD00Ndpk9GuEIAAAACIKT0+p6J0Tpm6MzW23jdLq0bPUe1TucGpYeSzgKMqbVAQAAAJ2sqtkeR5mJUW22K66uV73DKUlKZy+koCMcAQAAAJ3sSGnT80Z92glH+aW17uOM+LbboXMQjgAAAIBO1nyluj6Jtjbb5Zc1hagMRo6CjnAEAAAAdLLmK9W1N3JUUN585IhwFGwhD0dPPvmksrOzZbVaNXHiRH322Wftti8tLdVtt92mjIwMWSwWDRkyRCtXrgxStQAAAIDvvA1H+WVMqwulkK5Wt3z5ci1cuFBPP/20Jk6cqGXLlmnWrFnatWuXUlNbrsxRX1+vmTNnKjU1Vf/617+UmZmpQ4cOKSEhIfjFAwAAAF7KLW42rS6hnWl1zZ5NYkGG4AtpOHriiSd08803a/78+ZKkp59+WitWrNALL7yge+65p0X7F154QcXFxVq/fr3MZrMkKTs7O5glAwAAAD7LbfbM0fMf71e0JUJXjOujASkxHu08R44IR8EWsml19fX12rx5s2bMmNFUjNGoGTNmaMOGDa1e89Zbb2ny5Mm67bbblJaWphEjRuiRRx6Rw+EIVtkAAACAz5qvQvfXDYf01Np9unP5thbtTj5zFGeNULSFLUmDLWR/40VFRXI4HEpLS/M4n5aWpp07d7Z6zf79+/Xee+/pmmuu0cqVK7V371798Ic/lN1u1wMPPNDqNXV1daqrq3O/Li8vlyTZ7XbZ7fYAfRvfnbx3KGtA10F/gS/oL/AF/QW+oL/476zMOK3dXeRxrrquocXf5fD0WNnMJsVaI7r833M49RdvazC4XC5XJ9fSqry8PGVmZmr9+vWaPHmy+/xPf/pTffDBB/r0009bXDNkyBDV1tbqwIEDMplMkhqn5j366KPKz89v9T4PPviglixZ0uL8yy+/LJut7fmeAAAAQKA4nNKRaqmkzqAXdjf+Hjs8wanvn+EMcWU9Q3V1tb773e+qrKxMcXFxbbYL2chRr169ZDKZdPToUY/zR48eVXp6eqvXZGRkyGw2u4ORJJ1xxhkqKChQfX29IiMjW1yzaNEiLVy40P26vLxcWVlZuuiii9r9i+lsdrtdq1ev1syZM93PTwFtob/AF/QX+IL+Al/QX07flpxSvbC7cXXmsUP7afbsM0JcUecJp/5ycvZYR0IWjiIjIzVu3DitWbNGc+fOlSQ5nU6tWbNGCxYsaPWaqVOn6uWXX5bT6ZTR2Pi41O7du5WRkdFqMJIki8Uii8XS4rzZbA75Dymc6kDXQH+BL+gv8AX9Bb6gv/gvv7zefdwvOaZH/D2GQ3/x9v4h3edo4cKFevbZZ/XXv/5VX3/9tW699VZVVVW5V6+77rrrtGjRInf7W2+9VcXFxbrjjju0e/durVixQo888ohuu+22UH0FAAAAwGuHm61al5XEPkbhJqRLYMybN0/Hjh3T4sWLVVBQoNGjR2vVqlXuRRpycnLcI0SSlJWVpbffflt33XWXRo4cqczMTN1xxx362c9+FqqvAAAAAHgtt7hpH6Of/utz3f/mDk0dmKzHrhylP63dp7e25yk93qrFlw3X4LTYEFbaM4V8fcAFCxa0OY1u7dq1Lc5NnjxZn3zySSdXBQAAAAReZV2D+7i8tkGqbdAb2/L0w/MHaX9RlfYUVmpPYaUMhhAW2YOFPBwBAAAAPcX1U7J18HiVymrsKqyoU31D42p1CVFm5ZU2jSqlxzPlLhRC+swRAAAA0JNM6J+kFbdP08c/u0D9khq3lbFEGJUSa1F+WeMGsLGWCMWwAWxIEI4AAACAIHO5XDpc0jhSlJkYJZdLyi9reo3QIBwBAAAAQXa8ql41dockKSvRpsKKOtkdLklSZgLhKFQIRwAAAECQ5RZ7Lul9pLTpNSNHoUM4AgAAAIIst6Rp8YWsRJt7ip3EyFEoEY4AAACAIPMcObLpSLOV6hg5Ch3CEQAAABBkh0uahaNEm44wchQWWCMQAAAACLLc4qYw1CcxSt85u6/O7B2vI6XV6t8rOoSV9WyEIwAAACDIck+MHMVYIpRgMysxOlJn9YkPcVVgWh0AAAAQRA6nS3knnjHqkxglg8EQ4opwEuEIAAAACKKC8lr3nkZZSbYQV4PmCEcAAABAEB0u9lyMobiqXhv2HVducbXsDmcIKwPPHAEAAABB5LHHUVKUPjtQrB/8Y7MkaeHMIbr9wsGhKq3HY+QIAAAACKLcU0aOPPY4YhnvkCIcAQAAAEGU22yPoz5JUZ57HLEBbEgRjgAAAIAgOtxsj6PGkaOmsMTIUWgRjgAAAIAgOjlylBQdqWhLhHtandEgpcdbQ1laj0c4AgAAAIKkrsGhgvJaSVLWiSl0J6fVpcdZZTbx63ko8bcPAAAABEleaa1cjVscqU+STdX1DSqptkvieaNwQDgCAAAAguTg8Sr3cXayzXMxBp43CjnCEQAAABAkh4qawlG/5GgdLmWlunBCOAIAAACC5ODxppXp+iXZVFpdL7PJIKlx5TqEVkSoCwAAAAB6ikPNp9X1itbEAcn6xqhMHS2vVbSFX81DjZ8AAAAAECSHihtHjqxmo1JjLZIkk9Gg3jxvFBaYVgcAAAAEgcPpUu6JcJSdHC2DwRDiinAqRo4AAACAIMgrrZHd0biOd7/kpueL1u0t0vKNuR1ef8v0ARqRGd9p9YFwBAAAAATFoWaLMWQnR6uuwaE7X9mmzIQorfqyQPUOZ7vXzx3TWxLhqDMRjgAAAIAgaL7HUb/kaFkiTCqprtf/viwIYVVojnAEAAAABMEhj3DUOK3unzdPUl5ZrZxOV4fX94qxdFptaEQ4AgAAAILAY4+jE+HIYDAok5Xqwgar1QEAAABBkHMiHEWajMqI9z4QFVfVa2dBucpq7HK5Oh5hgv8IRwAAAEAnczpdOlTcOK0uKylKJqP3y3i/+9VRXbzsI41a8o5e+jSns0qECEcAAABApyusqFOtvXE1uuzkaJ+uzSurcR+nxVkDWhc8EY4AAACATnbqSnW+yC+tdR9nxBOOOhPhCAAAAOhkzVeqy+5la6dlS81HjnqzeEOnIhwBAAAAnaz5SnV9k3wLR/lljSNHlgijEm3mgNYFTyzlDQAAAHSyg0VNI0cZ8VGqtTs83jcZDTKbWo5buFwu5Zc2jhz1ToiSweD9Qg7wHeEIAAAA6GQHmoWjWcs+bPG+2WTQzy4eppumDfA4X17boKr6xiDF80adj2l1AAAAQCerOWWk6FR2h0tvbc9rcT6/2fNGvuyNBP8wcgQAAAB0sge/cab+uv6g6k4s531Std2h7bmlkqSUGEuL65qvVNc7gZGjzkY4AgAAADrZ+UNTdf7Q1BbnP91/XPP+/IkkqW9yy4UajpY3X8abkaPORjgCAAAAQiSnuP1V7L4zoa9mj8xQQVmtkqMjg1laj0Q4AgAAAEIkt4NwJElxVrPirCzhHQyEIwAAACBEDjULR9sPl6mosk6pcVadNySFZbtDgHAEAAAAhEjzkaPfr9njPn70ipG6cnxWKErq0VjKGwAAAAiRzMTWp9IdKa2Ry+XSA29+qSff36v3dh4NcmU9k9cjR59//rnXHzpy5Ei/igEAAAB6kqXfOkszzkhVTb1DH+w+pv99WSBJ6pNoU3FVvf664ZAkafqQFF0wLC2UpfYIXoej0aNHy2AwyOVytfr+yfcMBoMcjvY3uQIAAAAgxVgi9M3RmZKknQUV7vN9k2w6XNK0AWxWIst4B4PX4ejAgQOdWQcAAADQox0uaXr+KCspSlsOlbpf92lj+h0Cy+tw1K9fv86sAwAAAOjRcosbR4oiTUalxVo9wlIfRo6Cwutw9NZbb3n9od/4xjf8KgYAAADoiVwul3tDWJdcuua5T7W/qNL9/jMf7NMrG3N00fB0XT8lO0RVdn9eh6O5c+d61Y5njgAAAADfVNc7VGNv/B3a7nBpw/7jHu9/mVcuSVq397i+Maq3EqMjg15jT+D1Ut5Op9OrPwQjAAAAwDfRlgjNPivdq7bmCHbj6SxsAgsAAACEgaeuGae6BodcrsZpdmMfelc1docG9IpWXYNTR0prFB9lVoyFX+E7i99/s1VVVfrggw+Uk5Oj+vp6j/duv/320y4MAAAA6GksESZJ0vHKOvc0uz5JNq3fWyRJ6p3Awgydya9wtHXrVs2ePVvV1dWqqqpSUlKSioqKZLPZlJqaSjgCAAAATkOD06XLx2TqcEm1BvSK1oe7j0mSMglHncqvCYt33XWX5syZo5KSEkVFRemTTz7RoUOHNG7cOD322GOBrhEAAADoUdLirPrtvNF67QdTNGdUb/f5zARrCKvq/vwKR9u2bdOPf/xjGY1GmUwm1dXVKSsrS7/5zW/085//PNA1AgAAAD1WXmmN+5hpdZ3Lr3BkNptlNDZempqaqpycHElSfHy8cnNzA1cdAAAA0MMRjoLHr2eOxowZo40bN2rw4ME699xztXjxYhUVFenvf/+7RowYEegaAQAAgB7F6XTJaDRI8gxHD7y1Q0tXfi1zhFE3TMnW/Kn9Q1Vit+RXOHrkkUdUUVEhSXr44Yd13XXX6dZbb9XgwYP1/PPPB7RAAAAAoKe55HcfqaLWroGpMUqJsbjPF1c1rRL9+zV7CEcB5lc4Gj9+vPs4NTVVq1atClhBAAAAQE/mcrl0qLhKtXanoiJNunPGYO3IK1dpTWMwOlpeJ0mqqnPohy9tliTFR0XqzhmDlRbHgg2nw69wdODAATU0NGjw4MEe5/fs2SOz2azs7OxA1AYAAAD0OMer6lVrd0qS+iTaNK5fkt6+a7okqcHh1KB7/ydJqnc4tfKLAvd1RoP08OVnBb/gbsSvBRluuOEGrV+/vsX5Tz/9VDfccMPp1gQAAAD0WEdKmp4x6pPouQBDhMmo84emtHqdq1Or6hn83gR26tSpLc5PmjRJCxYsOO2iAAAAgJ7qcLNwdLS8Tv/8rHFl6AuGpSotzqoXbjhbxyrrdLikWv/4JEevbzkiSYqPMoek3u7Er5Ejg8HgXpChubKyMjkcjtMuCgAAAOipjpRWu4/f/fqoFr3+hRa9/oX2HauU1Pi7eGqsVccr7e5gJElrvj4a9Fq7G7/C0fTp07V06VKPIORwOLR06VKdc845ASsOAAAA6Gn6JNr8uq68tiHAlfQ8fk2r+/Wvf63p06dr6NChmjZtmiTpo48+Unl5ud57772AFggAAAD0JJeMSNc/bpzosb+RJA1KifF4Pbx3nEb3ide2w2WSpLRYi+wOpwxqfDYJvvMrHA0fPlyff/65/vjHP2r79u2KiorSddddpwULFigpKSnQNQIAAAA9hsFg0DmDe3XYLjMhyr1RrCRtP1ymwff+TwaDdNW4LP36ipGdWWa35Fc4kqTevXvrkUceCWQtAAAAAHxQa2/5vL/LJb22OVdLv3WWR3hCx/web/voo4907bXXasqUKTpypPFBsL///e/6+OOPA1YcAAAAgLadPyzVfdwvySazqTEMxVgiCEZ+8Csc/fvf/9asWbMUFRWlLVu2qK6ucZfesrIyRpMAAACAIIk0mdzH9156hiKMjb/ep8ZZQ1VSl+ZXOPrlL3+pp59+Ws8++6zM5qb11KdOnaotW7YErDgAAAAAbSsor3UfJ9giVXNiml1ptV33/ucL3fufL7R05dctFndA6/x65mjXrl2aPn16i/Px8fEqLS093ZoAAAAAeOE7Z2dpZJ945ZfVKjqyaRSpqLJOL32a436dU1ytP107LhQldil+haP09HTt3btX2dnZHuc//vhjDRgwIBB1AQAAAOjAqKwEjcpKkCTVNTjUL9mmQ8erW7SraWXhBrTkVzi6+eabdccdd+iFF16QwWBQXl6eNmzYoB//+MdavHhxoGsEAAAA0AFLhEnv3DVd+wqr5JJLB4uqddvLjY+89IqxhLi6rsGvcHTPPffI6XTqwgsvVHV1taZPny6LxaKf/OQnuummmwJdIwAAAAAvWCJMGt47TpJUVmN3nzdI2ltYIUmKj4pUSixhqTV+LchgMBh07733qri4WF9++aU++eQTHTt2TPHx8erfv3+gawQAAABwiopauz7df1w5x6tV19By2lxRZb37+LXNhzXjiQ8144kPdfbD7+qt7XnBLLXL8Ckc1dXVadGiRRo/frymTp2qlStXavjw4dqxY4eGDh2q3/3ud7rrrrs6q1YAAAAAJ3x5pFzz/vyJpj/6vh57e1eL9y0Rbf+qv25PUWeW1mX5NK1u8eLFeuaZZzRjxgytX79eV155pebPn69PPvlEjz/+uK688kqZmq21DgAAAKBzFJQ3Lc+dHh/V4v2ZZ6Tp57OHac/RyhPta/XRiVD07y2HteKLfElSVKRJ984+Q3PHZAah6vDmUzh67bXX9Le//U3f+MY39OWXX2rkyJFqaGjQ9u3bZTCwAy8AAAAQLAVlde7j9FY2fTUaDbpl+kD36/V7i9zhqMHpUmVdgySpsq5Bf9twkHAkH8PR4cOHNW5c4/roI0aMkMVi0V133UUwAgAAAIKsoKz5yFHLcHSqcdmJumJcH23PLZUkOVwu7T9WJUmKbGcKXk/iUzhyOByKjIxsujgiQjExMQEvCgAAAED78stq3ccZXoQjS4RJj105qtn1NZq89D1JUnyUOfAFdkE+hSOXy6UbbrhBFkvj0n+1tbX6wQ9+oOjoaI92r7/+euAqBAAAANDC0fLGcGQwyK+luZsv9X3oeLV7UQer2ahvjs5UVpItMIV2IT6Fo+uvv97j9bXXXhvQYgAAAAB45+TIkUHST17brmXfGePx/i/+31fafri0xXV9k2xa8s0zVVHb4D63s6BCOwsq3K//92WBVtw+rVPqDmc+haO//OUvnVUHAAAAAB+Unhj5cbqkHXnlLd7fU1ihzYdKWpzffKhEY/sl6uIz0xVrjfAISSflFFcHvuAuwKdwBAAAACA8fHdCX/39k0NyOF0+X2s8MRXvvR+fp91Hm0aMbv3HZpXXNijO2jOfQSIcAQAAAF3Qg984U4svG97m+3+dP8Hj9Z8+2KdHTzxXlBzduMhaSqzF43klu6MxaMVYemZM6JnfGgAAAOgGjMa2t9Q59b2Sqnr3caIt8tTmsjucqrE7JEkx1p4ZE1jQHAAAAOgBSqqbVqdLjmkZjqrqmp49iu2h4ahnfmsAAACgh3nsypFaPGe4SqrqlRpn0eZDxR7vHy2vcx/XNzjd75+RESdbZM+IDT3jWwIAAAA9nMFgUHyUWfFRZh2rqNO3/7Shzbbr9x3X+hPvr7j9HJ3ZOz5YZYYU0+oAAAAAtOmxt3fp/V2FoS4jKBg5AgAAAHqYqEiTbjqnv8e5I6U1+t+XBS3avr/rmD49UKwt98+U1WwKVokhQTgCAAAAepgYS4TuO2UZ8Or6Bn2VX65Dx1tuAFtd71BNvYNwBAAAAKD7s0VG6L0fn6e80hr3uZv+ulG7jlZKkow94IEcwhEAAAAASZLJaFBWks39+lhl0wp2ucXVis9suQR4d9ID8h8AAAAAf9Q3ON3H0RZzCCsJDkaOAAAAALTK7nC5j6MijHI6G18bDI1Lg3c3hCMAAAAArWpwNoWjSb96z32cmRClp68dp7P6dK/9j5hWBwAAAKBVxjYGh46U1uj1rYeDW0wQEI4AAAAAtCo11iqpMSSN65eooWmxIa6ocxGOAAAAALTq5GNFibZI/fvWKXrwG2e637NEdL89jwhHAAAAAFpVXe+QJNksjUGotsHhfs9q7n5Rovt9IwAAAAABUVXXIEmKjmxcx63O3jwcMXIEAAAAoAdwOF2qO7HPkS3yxMiRvWnfI2tE94sSLOUNAAAAoAWT0aC9D1+iartDDSf2O6prNq3O0g1HjghHAAAAAFoVYTIqztQ0QuQxcsQzRwAAAAB6qtrmzxyxWh0AAACAnspz5Kj7hSOm1QEAAABo4UBRlf75WY5skSZNGpCsSQOSPZbytrAgAwAAAICe4GBRlf784X5J0l0zDJo0IFl1zUaOuuOCDN0v7gEAAAA4bVX1De7jaDaBBQAAANBTVdc1BSHbiU1ga9kEFgAAAEBP09rIUV03X5CBcAQAAACgher69keOuuOCDN3vGwEAAAA4bVV1zUaOIk+MHDUwcgQAAACgh/EYObK08swRI0cAAAAAeoLmI0e2SM/V6iKMBkWYul+U6H7fCAAAAMBpq2wWjmKtJ0eOGqfVdcfnjSQ2gQUAAADQisFpsSqprldlXYNirWZJTdPquuPzRhLhCAAAAEArFs4c0uLcyQUZums46p7jYQAAAAAC7uTIkcXcPWNE9/xWAAAAAAKuzv3MESNHAAAAAHooh9OlesfJaXXdM0bwzBEAAAAADw6nSxc+vlbRlgiN6ZugX849S3UNzfc46p4jR4QjAAAAAB6q6ht08Hi1JCkpOlJS05Q6qfuOHHXPbwUAAADAbxW1rexx1HzkiNXqOs+TTz6p7OxsWa1WTZw4UZ999plX173yyisyGAyaO3du5xYIAAAA9CCVzcJRjMVzA1ip+24CG/JvtXz5ci1cuFAPPPCAtmzZolGjRmnWrFkqLCxs97qDBw/q7rvv1rRp04JUKQAAANAzVNbZ3cenbgArMXLUaZ544gndfPPNmj9/voYPH66nn35aNptNL7zwQpvXOBwOXXPNNVqyZIkGDBgQxGoBAACA7q+ilZGjkxvASoSjTlFfX6/NmzdrxowZ7nNGo1EzZszQhg0b2rzuF7/4hVJTU3XjjTcGo0wAAACgR6msa+WZo2YjR911Wl1IV6srKiqSw+FQWlqax/m0tDTt3Lmz1Ws+/vhjPf/889q2bZtX96irq1NdXZ37dXl5uSTJbrfLbre3dVmnO3nvUNaAroP+Al/QX+AL+gt8QX/pOUqrmn5/joowyG63q7Km6ZzFZOiwH4RTf/G2hi61lHdFRYW+973v6dlnn1WvXr28umbp0qVasmRJi/PvvPOObDZboEv02erVq0NdAroQ+gt8QX+BL+gv8AX9pfvbmGeQ1Dh1bs9XX2hl4efadrzp3MF9u7WydpdXnxUO/aW6utqrdiENR7169ZLJZNLRo0c9zh89elTp6ekt2u/bt08HDx7UnDlz3Oeczsa5jxEREdq1a5cGDhzocc2iRYu0cOFC9+vy8nJlZWXpoosuUlxcXCC/jk/sdrtWr16tmTNnymw2h6wOdA30F/iC/gJf0F/gC/pLz7FnzV7p0H5J0vTJZ2va4F6yb8uTdn8pSco39tJmV6y7fZw1QleN76OMeKv7XDj1l5OzxzoS0nAUGRmpcePGac2aNe7luJ1Op9asWaMFCxa0aD9s2DB98cUXHufuu+8+VVRU6He/+52ysrJaXGOxWGSxWFqcN5vNIf8hhVMd6BroL/AF/QW+oL/AF/SX7u/C4elKjLGqsrZBg9PjZTab5ZDB/f7GgyXaeLDE45qdR6v03PXjW3xWOPQXb+8f8ml1Cxcu1PXXX6/x48drwoQJWrZsmaqqqjR//nxJ0nXXXafMzEwtXbpUVqtVI0aM8Lg+ISFBklqcBwAAAOCfMX0TNaZvose5SQOSZYs0qbre0eo1h0u8m7oWzkIejubNm6djx45p8eLFKigo0OjRo7Vq1Sr3Ig05OTkyGrvnahgAAABAV9EvOVqf/PxC7T9W5XH+W0+tk9MlRZgMbVzZdYQ8HEnSggULWp1GJ0lr165t99oXX3wx8AUBAAAAaCHOatborAT3a5fLJaer8dhs6voDGmERjgAAAACEj5zj1YowGRRjjVCcte3ndewOl/uYcAQAAACg27nxrxu1p7BS0ZEm7fjFxW22szuc7mNzN5hW1/XjHQAAAICAqqhtkCTFWNsfS/EMR10/WnT9bwAAAAAgoCrrGsNRbDtT6iTPaXUR3WARta7/DQAAAAAEjMPpcoejGIv3I0eREUyrAwAAANCNVNU3uI9jO5hW19DNFmTo+t8AAAAAQMCU19jdx+2tVCdJ9c1GjphWBwAAAKBbKa9pGjmKi2JaHQAAAIAeqrzW+5GjBhZkAAAAANBdeUyri/J+Wl13eOaITWABAAAAuJXXNptWd2JBhq/zy7X7aEWLtvsKK93Hh45X6aM9xzRtcErnF9lJCEcAAAAA3C4bmaFJA5JUXtOg1DiLJGnlF/n6w3t7271uzc5CldXYCUcAAAAAuger2aQ+iTYpMdSVBB/hCAAAAEC7zhuaqqToyBbnd+ZXaPmmXEnSBcNS9e2xfSRJ7+08qj+t3afi4yZZBx7TrBG9g1qvvwhHAAAAANo1rl+ixvVrOZS04vN8dziaPCBZl47MkCQdq6jTxoMlkgwqqqgLZqmnpesvKQEAAAAgJBqczTaBNbHPEQAAAIAeqr6hey3l3fW/AQAAAICQaHA2bQJrZuQIAAAAQE9lZxNYAAAAAJDsjqaRo/yyWn1xuEySdLikJlQlnRbCEQAAAAC/NB85evTtXXr07V0t2pRW24NZ0mnp+mNfAAAAAEKiT2JUh232HqsKQiWBwcgRAAAAAL/MOjNdD18+QrsKKjzOf7ynSPuLGkORS67WLg1LhCMAAAAAfjGbjLpmYr8W5x9/Z6f+8N4+SVJGnDXYZfmNaXUAAAAAAqpPoq3ZccdT78IF4QgAAAAARDgCAAAAAEmEIwAAAAAB5nC6Wj0Od4QjAAAAAAG1+VCJ+3hLbmnoCvER4QgAAAAARDgCAAAAAEmEIwAAAACQRDgCAAAAAEmEIwAAAACQRDgCAAAAAEmEIwAAAACQRDgCAAAAAEmEIwAAAACQRDgCAAAAEGDD0mPdx0PTYkJYiW8IRwAAAAACKi7K3HRsNbfTMrwQjgAAAABAhCMAAAAAkEQ4AgAAABBgJVX1TcfV9e20DC+EIwAAAAABtaew0n2891hVCCvxDeEIAAAAAEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAAWY0GJqOZWinZXghHAEAAAAIqPHZie7jcf0SQleIjwhHAAAAACDCEQAAAABIIhwBAAAAgCTCEQAAAIAAO1hU5T4+dLw6hJX4hnAEAAAAIKAKK+qajivr2mkZXghHAAAAACDCEQAAAABIIhwBAAAAgCTCEQAAAABIIhwBAAAAgCTCEQAAAABIIhwBAAAAgCTCEQAAAABIIhwBAAAACLAEm7npOMrcTsvwQjgCAAAAEFBD0mLdx4NTY0JYiW8IRwAAAAAgwhEAAAAASCIcAQAAAIAkwhEAAACAANt+uNR9/PmRstAV4iPCEQAAAICAqrM7m44bnO20DC+EIwAAAAAQ4QgAAAAAJBGOAAAAAEAS4QgAAAAAJBGOAAAAAEAS4QgAAAAAJBGOAAAAAEAS4QgAAAAAJBGOAAAAAARYv2Rb03GirZ2W4YVwBAAAACCg0uKs7uPUOEsIK/EN4QgAAAAARDgCAAAAAEmEIwAAAAABVmN3uI9rmx2HO8IRAAAAgID64nBZ03FeeQgr8Q3hCAAAAABEOAIAAAAASYQjAAAAAJBEOAIAAAAASYQjAAAAAJBEOAIAAAAASYQjAAAAAJBEOAIAAAAASYQjAAAAAJBEOAIAAAAQYCP7xLuPz+odF8JKfEM4AgAAABBQVrOp1eNwRzgCAAAAABGOAAAAAEAS4QgAAABAgB0tr231ONwRjgAAAAAE1KHj1e7jnJKaEFbiG8IRAAAAAIhwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAAsxqNjUdR3SdyNF1KgUAAADQJYzsE+8+Piszvp2W4YVwBAAAAAAiHAEAAACAJMIRAAAAAEgiHAEAAAAIsN1HK9zHeworQ1iJbwhHAAAAAAKqtNredFxjb6dleCEcAQAAAIAIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAIMBS4yxNx7GWdlqGF8IRAAAAgIDKTo52H/dLsoWwEt8QjgAAAABAYRKOnnzySWVnZ8tqtWrixIn67LPP2mz77LPPatq0aUpMTFRiYqJmzJjRbnsAAAAA8EbIw9Hy5cu1cOFCPfDAA9qyZYtGjRqlWbNmqbCwsNX2a9eu1dVXX633339fGzZsUFZWli666CIdOXIkyJUDAAAA6E5CHo6eeOIJ3XzzzZo/f76GDx+up59+WjabTS+88EKr7V966SX98Ic/1OjRozVs2DA999xzcjqdWrNmTZArBwAAANCajQeL3cebDpWEsBLfhDQc1dfXa/PmzZoxY4b7nNFo1IwZM7RhwwavPqO6ulp2u11JSUmdVSYAAAAAH7hczY5DV4bPIkJ586KiIjkcDqWlpXmcT0tL086dO736jJ/97Gfq3bu3R8Bqrq6uTnV1de7X5eXlkiS73S673e5n5afv5L1DWQO6DvoLfEF/gS/oL/AF/QXecjmdHseh7jPe3j+k4eh0/epXv9Irr7yitWvXymq1ttpm6dKlWrJkSYvz77zzjmy20C8ruHr16lCXgC6E/gJf0F/gC/oLfEF/QUdyDxt1cpJaXl6+Vq4M7foA1dXVXrULaTjq1auXTCaTjh496nH+6NGjSk9Pb/faxx57TL/61a/07rvvauTIkW22W7RokRYuXOh+XV5e7l7EIS4u7vS+wGmw2+1avXq1Zs6cKbPZHLI60DXQX+AL+gt8QX+BL+gv8NYH//5CG4vyJUm9e2do9uxRIa3n5OyxjoQ0HEVGRmrcuHFas2aN5s6dK0nuxRUWLFjQ5nW/+c1v9PDDD+vtt9/W+PHj272HxWKRxdJyV16z2RwW/1CHSx3oGugv8AX9Bb6gv8AX9Bd0xGA0ehyHur94e/+QT6tbuHChrr/+eo0fP14TJkzQsmXLVFVVpfnz50uSrrvuOmVmZmrp0qWSpF//+tdavHixXn75ZWVnZ6ugoECSFBMTo5iYmJB9DwAAAABdW8jD0bx583Ts2DEtXrxYBQUFGj16tFatWuVepCEnJ0fGZsnzT3/6k+rr63XFFVd4fM4DDzygBx98MJilAwAAAOhGQh6OJGnBggVtTqNbu3atx+uDBw92fkEAAAAAepyQbwILAAAAAOGAcAQAAAAgoAanNa0FMCglOoSV+IZwBAAAACCgEm2RrR6HO8IRAAAAAIhwBAAAAACSCEcAAAAAAqy8xt7qcbgjHAEAAAAIqJ0FFe7jXYWVIazEN4QjAAAAABDhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAECAjc9OdB+P65sQukJ8RDgCAAAAEFBGg6HV43BHOAIAAAAAEY4AAAAAQBLhCAAAAECA5RZXNx2X1ISwEt8QjgAAAAAEVH5Zrfu4oLy2nZbhhXAEAAAAACIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAACAAIuzRriPYy0R7bQML4QjAAAAAAE1LCOu6Tg9NoSV+IZwBAAAAAAiHAEAAACAJMIRAAAAAEgiHAEAAAAIsC+PlLmPd+SVh7AS3xCOAAAAAARUdb2j6djuaKdleCEcAQAAAIAIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAIMD6JEY1HSdEtdMyvBCOAAAAAARU72aBKCPeGsJKfEM4AgAAAAARjgAAAABAEuEIAAAAQIDZHc5Wj8Md4QgAAABAQG3NKXUfbztcFrpCfEQ4AgAAAAARjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAAAE2Jm949zHw9NjQ1iJbwhHAAAAAAIq2hLR6nG4IxwBAAAAgAhHAAAAACCJcAQAAAAgwIoq6pqOK+vaaRleCEcAAAAAAmp/UZX7+MDx6hBW4hvCEQAAAACIcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAAALMbDI0HRsN7bQML4QjAAAAAAE1pm+i+3h0VkLoCvER4QgAAAAARDgCAAAAAEmEIwAAAACQRDgCAAAAEGD7jlW6j/cfqwphJb4hHAEAAAAIqOOV9U3H1fXttAwvhCMAAAAAEOEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAAAEWK+YSPdxcnRkOy3DC+EIAAAAQEANSIlpOu4VHcJKfEM4AgAAAAARjgAAAABAEuEIAAAAACQRjgAAAAAE2JacEvfx1tzS0BXiI8IRAAAAgIBqcLiajp2udlqGF8IRAAAAAIhwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAIIlwBAAAAACSCEcAAAAAAmxASnTTcXJ0Oy3DC+EIAAAAQED1irG4j5NjIkNYiW8IRwAAAAAgwhEAAAAASCIcAQAAAAiwqrqGVo/DHeEIAAAAQEDtyCt3H39VUBHCSnxDOAIAAAAAEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAAAkSRGhLgAAAACQJIfDIbvdHuoyEABxZpcyY03u49ra2k69n9lslslkOu3PIRwBAAAgpFwulwoKClRaWhrqUhAgM7OMmpKWKkmyRZp04MCBTr9nQkKC0tPTZTAY/P4MwhEAAABC6mQwSk1Nlc1mO61fbhEerKU1Kq9tHAWMtUaod4Kt0+7lcrlUXV2twsJCSVJGRobfn0U4AgAAQMg4HA53MEpOTg51OQiQiEinDA2GE8dmWa3WTr1fVFSUJKmwsFCpqal+T7FjQQYAAACEzMlnjGy2zhtZQPDZIpvCic18+s8CeXXPE33odJ5bIxwBAAAg5JhK1700/3EG62cbiPsQjgAAAABAhCMAAAAgbGRnZ2vZsmWhLiMgRmUl6r1VKyRJBw8elMFg0LZt20JbVAcIRwAAAICPDAZDu38efPBBvz5348aNuuWWW06rtvPOO8+jlrS0NF155ZU6dOjQaX2uL+wOV7Njp7KyspSfn68RI0YErQZ/EI4AAAAAH+Xn57v/LFu2THFxcR7n7r77bndbl8ulhoYGrz43JSUlIItT3HzzzcrPz1deXp7efPNN5ebm6tprrz3tz/VWfYOz6djhlMlkUnp6uiIiwnuxbMIRAAAA4KP09HT3n/j4eBkMBvfrnTt3KjY2Vv/73/80btw4WSwWffzxx9q3b5+++c1vKi0tTTExMTr77LP17rvvenzuqdPqDAaDnnvuOV1++eWy2WwaPHiw3nrrrQ7rs9lsSk9PV0ZGhiZNmqQFCxZoy5Yt7vcdDoduvPFG9e/fX1FRURo6dKh+97vfeXzG2rVrNWHCBEVHRyshIUFTp071GH168803NXbsWFmtVg0YMEBLlixpMwSeOq1u7dq1MhgMWrNmjcaPHy+bzaYpU6Zo165dHtf5co9ACO/oBgAAgB5pzh8+1rGKuqDfNyXWov/3o3MC8ln33HOPHnvsMQ0YMECJiYnKzc3V7Nmz9fDDD8tisehvf/ub5syZo127dqlv375tfs6SJUv0m9/8Ro8++qj+8Ic/6JprrtGhQ4eUlJTkVR3FxcV69dVXNXHiRPc5p9OpPn366LXXXlNycrLWr1+vW265RRkZGbrqqqvU0NCguXPn6uabb9Y///lP1dfX67PPPnOvCPfRRx/puuuu0+9//3tNmzZN+/btc08HfOCBB7z+O7r33nv1+OOPKyUlRT/4wQ/0f//3f1q3bl1A7+ELwhEAAADCzrGKOhWU14a6jNPyi1/8QjNnznS/TkpK0qhRo9yvH3roIf3nP//RW2+9pQULFrT5OTfccIOuvvpqSdIjjzyi3//+9/rss8908cUXt3nNU089peeee04ul0vV1dUaMmSI3n77bff7ZrNZS5Yscb/u37+/NmzYoFdffVVXXXWVysvLVVZWpssuu0wDBw6UJJ1xxhnu9kuWLNE999yj66+/XpI0YMAAPfTQQ/rpT3/qU3B5+OGHde6550pqDJOXXnqpamtrZbVaA3YPXxCOAAAAEHZSYi1d/r7jx4/3eF1ZWakHH3xQK1asUH5+vhoaGlRTU6OcnJx2P2fkyJHu4+joaMXFxamwsLDda6655hrde++9kqSjR4/qkUce0UUXXaTNmzcrNjZWkvTkk0/qhRdeUE5OjmpqalRfX6/Ro0dLagxyN9xwg2bNmqWZM2dqxowZuuqqq5SRkSFJ2r59u9atW6eHH37YfU+Hw6Ha2lpVV1d79xd0ync7+dmFhYXq27dvh/fojI2DwyIcPfnkk3r00UdVUFCgUaNG6Q9/+IMmTJjQZvvXXntN999/vw4ePKjBgwfr17/+tWbPnh3EigEAANCZAjW1LZSio6M9Xt99991avXq1HnvsMQ0aNEhRUVG64oorVF9f3+7nmM1mj9cGg0FOp7ON1o3i4+M1aNAgSdKgQYP0/PPPKyMjQ8uXL9dNN92kV155RXfffbcef/xxTZ48WbGxsXr00Uf16aefuj/jL3/5i26//XatWrVKy5cv13333afVq1dr0qRJqqys1JIlS/Stb32rxb2tVqtU692oX/PvdnLK3snv1uE9OkHIw9Hy5cu1cOFCPf3005o4caKWLVumWbNmadeuXUpNTW3Rfv369br66qu1dOlSXXbZZXr55Zc1d+5cbdmyJeyXBgQAAEDPtW7dOt1www26/PLLJTX+8n/w4MGg3NtkMkmSampq3LVMmTJFP/zhD91t9u3b1+K6MWPGaMyYMVq0aJEmT56sl19+WZMmTdLYsWO1a9cudwDrDMG4x6lCvlrdE088oZtvvlnz58/X8OHD9fTTT8tms+mFF15otf3vfvc7XXzxxfrJT36iM844Qw899JDGjh2rP/7xj0GuHAAAAPDe4MGD9frrr2vbtm3avn27vvvd73Y4AuSv6upqFRQUqKCgQNu3b9ett94qq9Wqiy66yF3Lpk2b9Pbbb2v37t26//77tXHjRvf1Bw4c0KJFi7RhwwYdOnRI77zzjvbs2eN+7mjx4sX629/+piVLlmjHjh36+uuv9corr+i+++4L2HcIxj1OFdJwVF9fr82bN2vGjBnuc0ajUTNmzNCGDRtavWbDhg0e7SVp1qxZbbYHAAAAwsETTzyhxMRETZkyRXPmzNGsWbM0duzYTrnXs88+q4yMDGVkZOj8889XUVGRVq5cqaFDh0qSvv/97+tb3/qW5s2bp4kTJ+r48eMeo0g2m007d+7Ut7/9bQ0ZMkS33HKLbrvtNn3/+9+X1Pj793//+1+98847OvvsszVp0iT99re/Vb9+/QL2HYJxj1OFdFpdUVGRHA6H0tLSPM6npaVp586drV5TUFDQavuCgoJW29fV1amurmkZyPLyckmS3W6X3W4/nfJPy8l7h7IGdB30F/iC/gJf0F/gi87oL3a7XS6XS06ns9NGUTrbddddp+uuu85d//Tp0+VwOCTJ4zv17du3xb5Gt956q0e7/fv3e7xu7XOKi4tbnGvuvffea7PWk9eYzWY9//zzev755z3ef/jhh+V0OpWSkqJ///vf7X7GzJkzPVbja/6+yShtzy2RJJkMBvXp29fju7T2dzRy5MgW59q7R2vnXC6X7Ha7exrhSd722ZA/c9TZli5d6rFM4UnvvPNOp6xw4avVq1eHugR0IfQX+IL+Al/QX+CLQPaXiIgIpaenq7KyssOFCdB1OJtlEVdDvcrLO/9nW19fr5qaGn344YctNor1dgW9kIajXr16yWQy6ejRox7njx49qvT09FavSU9P96n9okWLtHDhQvfr8vJyZWVl6aKLLlJcXNxpfgP/2e12rV69WjNnzmyxAglwKvoLfEF/gS/oL/BFZ/SX2tpa5ebmKiYmptNWIEPwxbikFKdTFRWVio+Llclo6PR71tbWKioqStOnT2/Rl07OHutISMNRZGSkxo0bpzVr1mju3LmSGofD1qxZ0+ZGWJMnT9aaNWt05513us+tXr1akydPbrW9xWKRxdJyvXqz2RwW/xEIlzrQNdBf4Av6C3xBf4EvAtlfHA6HDAaDjEajjMaQrxWGADFKMhqkCKNkMhqC8rM1Go0yGAyt9k9v+2vIp9UtXLhQ119/vcaPH68JEyZo2bJlqqqq0vz58yU1zuHMzMzU0qVLJUl33HGHzj33XD3++OO69NJL9corr2jTpk3685//HMqvAQAAAKCLC3k4mjdvno4dO6bFixeroKBAo0eP1qpVq9yLLuTk5HgkzSlTpujll1/Wfffdp5///OcaPHiw3njjDfY4AgAAAHBaQh6OJGnBggVtTqNbu3Zti3NXXnmlrrzyyk6uCgAAAEBPwsROAAAAABDhCAAAAAAkEY4AAAAA+Gnt2rUyGAwqLS2VJL344otKSEgIaU2ng3AEAAAA+MhgMLT758EHHzytz37jjTd8qiEiIkJ9+/bVwoULVVdX5/e9T9e8efO0e/fukN3/dIXFggwAAABAV5Kfn+8+Xr58uRYvXqxdu3a5z8XExASljr/85S+6+OKLZbfbtX37ds2fP1/R0dF66KGHgnL/U0VFRSkqKiok9w4ERo4AAAAAH6Wnp7v/xMfHy2AweJx75ZVXdMYZZ8hqtWrYsGF66qmn3NfW19drwYIFysjIkNVqVb9+/dx7emZnZ0uSLr/8chkMBvfrtiQkJCg9PV1ZWVm67LLL9M1vflNbtmxxv79v3z5985vfVFpammJiYnT22Wfr3Xff9fiMp556SoMHD5bValVaWpquuOIK93tOp1NLly5V//79FRUVpVGjRulf//pXm/WcOq3uV7/6lcaOHau///3vys7OVnx8vL7zne+ooqLC73t0JkaOAAAAgAB66aWXtHjxYv3xj3/UmDFjtHXrVt18882Kjo7W9ddfr9///vd666239Oqrr6pv377Kzc1Vbm6uJGnjxo1KTU11jwiZTCav77t792699957uuGGG9znKisrNXv2bD388MOyWCz629/+pjlz5mjXrl3q27evNm3apNtvv11///vfNWXKFBUXF+ujjz5yX7906VL94x//0NNPP63Bgwfrww8/1LXXXquUlBSde+65XtW1b98+vfHGG/rvf/+rkpISXXXVVfrVr36lhx9+OGD3CBTCEQAAAMLScx/t13MfHeiw3YjMOD13/dke527660Z9eaS8w2tvmtZfN00b4HeNrXnggQf0+OOP61vf+pYkqX///vrqq6/0zDPP6Prrr1dOTo4GDx6sc845RwaDQf369XNfm5KSIqlpRKgjV199tUwmkxoaGlRXV6fLLrtMixYtcr8/atQojRo1yv36oYce0n/+8x+99dZbWrBggXJychQdHa3LLrtMsbGx6tevn8aMGSNJqqur0yOPPKJ3331XkydPliQNGDBAH3/8sZ555hmvg4vT6dSLL76o2NhYSdL3vvc9rVmzRg8//HDA7hEohCMAAACEpYraBhWU13bYLiPB2uLc8ap6r66tqG3wq7a2VFVVad++fbrxxht18803u883NDQoPj5eknTDDTdo5syZGjp0qC6++GJddtlluuiii/y6329/+1vNmDFDDodDe/fu1cKFC/W9731Pr7zyiqTGkaMHH3xQK1asUH5+vhoaGlRTU6OcnBxJ0syZM9WvXz8NGDBAF198sS6++GJdfvnlstls2rt3r6qrqzVz5kyPe9bX17sDlDeys7PdwUiSMjIyVFhYKEkBu0egEI4AAAAQlmKtEUqPaxl8TpUcHdnqOW+ujbUG9tfhyspKSdKzzz6riRMnerx3corc2LFjdeDAAf3vf//Tu+++q6uuukozZszw6zmb9PR0DRo0SJI0dOhQVVRU6Oqrr9Yvf/lLDRo0SHfffbdWr16txx57TIMGDVJUVJSuuOIK1dfXS5JiY2O1ZcsWrV27Vu+8844WL16sBx98UBs3bnR/lxUrVigzM9PjvhaLxesazWazx2uDwSCn0ylJAbtHoBCOAAAAEJZumjbA7ylvp06zC5a0tDT17t1b+/fv1zXXXNNmu7i4OM2bN0/z5s3TFVdcoYsvvljFxcVKSkqS2WyWw+Hw6/4nA1hNTY0kad26dbrhhht0+eWXS2oMIwcPHvS4JiIiQjNmzNCMGTP0wAMPKCEhQe+9955mzpwpi8WinJycTpveNnz48E6/hy8IRwAAAEAALVmyRLfffrvi4+N18cUXq66uTps2bVJJSYkWLlyoJ554QhkZGRozZoyMRqNee+01paenu1d5y87O1po1azR16lRZLBYlJia2ea/S0lIVFBTI6XRqz549+sUvfqEhQ4bojDPOkCQNHjxYr7/+uubMmSODwaD777/fPWojSf/973+1f/9+TZ8+XYmJiVq5cqWcTqeGDh2q2NhY3X333brrrrvkdDp1zjnnqKysTOvWrVNcXJyuv/760/67CsY9fEE4AgAAAALopptuks1m06OPPqqf/OQnio6O1llnnaU777xTUmMg+M1vfqM9e/bIZDLp7LPP1sqVK2U0Nu6y8/jjj2vhwoV69tlnlZmZ2WKkp7n58+dLknsp8enTp+uRRx5RRETjr/lPPPGE/u///k9TpkxRr1699LOf/Uzl5U0LVSQkJOj111/Xgw8+qNraWg0ePFj//Oc/deaZZ0pqXMAhJSVFS5cu1f79+5WQkKCxY8fq5z//ecD+voJxD28ZXC6XK+h3DaHy8nLFx8errKxMcXFxIavDbrdr5cqVmj17dot5mMCp6C/wBf0FvqC/wBed0V9qa2t14MAB9e/fX1Zrx88IoetwOp0qLy9XXFycO/h1pvb6krcZgE1gAQAAAECEIwAAAACQRDgCAAAAAEmEIwAAAACQRDgCAAAAAEmEIwAAAISBHraAMjpBIPoQ4QgAAAAhc3JJ8Orq6hBXgq7uZB86nWXm2QQWAAAAIWMymZSQkKDCwkJJks1mk8FgCHFVCASn06n6+nrV1tZ26j5HLpdL1dXVKiwsVEJCgkwmk9+fRTgCAABASKWnp0uSOyChe3C5XKqpqVFUVFRQAm9CQoK7L/mLcAQAAICQMhgMysjIUGpqqux2e6jLQYDY7XZ9+OGHmj59+mlNdfOG2Ww+rRGjkwhHAAAACAsmkykgv+AiPJhMJjU0NMhqtXZ6OAoUFmQAAAAAABGOAAAAAEAS4QgAAAAAJPXAZ45Obg5VXl4e0jrsdruqq6tVXl7eZeZgInToL/AF/QW+oL/AF/QX+CKc+svJ3/072ii2x4WjiooKSVJWVlaIKwEAAAAQTBUVFYqPj2/zfYOro/jUzTidTuXl5Sk2NjakG4yVl5crKytLubm5iouLC1kd6BroL/AF/QW+oL/AF/QX+CKc+ovL5VJFRYV69+7d7oa0PW7kyGg0qk+fPqEuwy0uLi7knQVdB/0FvqC/wBf0F/iC/gJfhEt/aW/E6CQWZAAAAAAAEY4AAAAAQBLhKGQsFoseeOABWSyWUJeCLoD+Al/QX+AL+gt8QX+BL7pif+lxCzIAAAAAQGsYOQIAAAAAEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhqFM9+eSTys7OltVq1cSJE/XZZ5+12/61117TsGHDZLVaddZZZ2nlypVBqhThwJf+8uyzz2ratGlKTExUYmKiZsyY0WH/Qvfi679fTnrllVdkMBg0d+7czi0QYcXX/lJaWqrbbrtNGRkZslgsGjJkCP9N6kF87S/Lli3T0KFDFRUVpaysLN11112qra0NUrUIpQ8//FBz5sxR7969ZTAY9MYbb3R4zdq1azV27FhZLBYNGjRIL774YqfX6QvCUSdZvny5Fi5cqAceeEBbtmzRqFGjNGvWLBUWFrbafv369fr/7dx7TFPnHwbwpxRKuZQgMmhZEANuSjrnIqJBXAzKBMccZDE0zjQlwbHNolt2ZTNLiVdmmFkUZZk4cJl3MheCTJSuZI6xZFFYMMMql85dRGdcMsSxFvr+/rIbWhbbn+0p+HyS/tG37znnOc035Xx5T7tq1SoUFxejo6MDBQUFKCgowPnz5/2cnKTgab20trZi1apVsFgsaG9vR2JiIpYtW4Zff/3Vz8lJCp7Wy202mw1vvPEGnnzyST8lpUDgab3Y7XY89dRTsNlsqK+vh9Vqxd69e/Hwww/7OTlJwdN6OXjwIMrKymAymdDd3Y19+/bhyJEjePfdd/2cnKQwNDSEOXPmYPfu3fc0v7+/H3l5ecjKykJnZydeffVVrFmzBs3NzT5O6gFBPjF//nxhNBpdz0dHR0VCQoLYtm2b2/mFhYUiLy9vzNiCBQvEiy++6NOcFBg8rZc7jYyMCJVKJfbv3++riBRAvKmXkZERsXDhQlFTUyMMBoPIz8/3Q1IKBJ7WS3V1tUhOThZ2u91fESmAeFovRqNRLFmyZMzYa6+9JjIzM32akwIPAHH8+PH/nPPWW28JrVY7Zkyn04mcnBwfJvMMV458wG634+zZs8jOznaNBQUFITs7G+3t7W63aW9vHzMfAHJycsadT5OHN/Vyp1u3bsHhcCAmJsZXMSlAeFsvGzduRFxcHIqLi/0RkwKEN/XS0NCAjIwMGI1GxMfH47HHHsPWrVsxOjrqr9gkEW/qZeHChTh79qzr1ru+vj40NTXh6aef9ktmmlgmwvVusNQBJqPr169jdHQU8fHxY8bj4+Nx4cIFt9sMDAy4nT8wMOCznBQYvKmXO7399ttISEi46wOHJh9v6uWbb77Bvn370NnZ6YeEFEi8qZe+vj589dVXWL16NZqamtDT04O1a9fC4XDAZDL5IzZJxJt6ef7553H9+nUsWrQIQgiMjIzgpZde4m115NZ417t//vkn/vrrL4SFhUmU7B9cOSKa4CoqKnD48GEcP34cSqVS6jgUYAYHB6HX67F3717ExsZKHYcmAKfTibi4OHz88cdIS0uDTqfDhg0b8NFHH0kdjQJQa2srtm7dij179uDcuXP4/PPPceLECWzatEnqaERe4cqRD8TGxkIul+Pq1atjxq9evQq1Wu12G7Va7dF8mjy8qZfbKisrUVFRgZaWFjz++OO+jEkBwtN66e3thc1mw4oVK1xjTqcTABAcHAyr1YqUlBTfhibJePP5otFoEBISArlc7hpLTU3FwMAA7HY7FAqFTzOTdLypl/feew96vR5r1qwBAMyePRtDQ0MoKSnBhg0bEBTE/8PTP8a73o2KigqIVSOAK0c+oVAokJaWBrPZ7BpzOp0wm83IyMhwu01GRsaY+QBw+vTpcefT5OFNvQDA9u3bsWnTJpw8eRLz5s3zR1QKAJ7Wy6xZs9DV1YXOzk7X49lnn3X9UlBiYqI/45OfefP5kpmZiZ6eHlcTDQAXL16ERqNhYzTJeVMvt27duqsBut1YCyF8F5YmpAlxvSv1L0JMVocPHxahoaGirq5O/Pjjj6KkpERER0eLgYEBIYQQer1elJWVuea3tbWJ4OBgUVlZKbq7u4XJZBIhISGiq6tLqlMgP/K0XioqKoRCoRD19fXiypUrrsfg4KBUp0B+5Gm93Im/Vvdg8bReLl++LFQqlSgtLRVWq1U0NjaKuLg4sXnzZqlOgfzI03oxmUxCpVKJQ4cOib6+PnHq1CmRkpIiCgsLpToF8qPBwUHR0dEhOjo6BACxY8cO0dHRIX766SchhBBlZWVCr9e75vf19Ynw8HDx5ptviu7ubrF7924hl8vFyZMnpTqFu7A58qFdu3aJadOmCYVCIebPny++++4712uLFy8WBoNhzPyjR4+KRx99VCgUCqHVasWJEyf8nJik5Em9JCUlCQB3PUwmk/+DkyQ8/Xz5NzZHDx5P6+Xbb78VCxYsEKGhoSI5OVls2bJFjIyM+Dk1ScWTenE4HKK8vFykpKQIpVIpEhMTxdq1a8Uff/zh/+DkdxaLxe31yO0aMRgMYvHixXdt88QTTwiFQiGSk5NFbW2t33P/F5kQXPMkIiIiIiLid46IiIiIiIjA5oiIiIiIiAgAmyMiIiIiIiIAbI6IiIiIiIgAsDkiIiIiIiICwOaIiIiIiIgIAJsjIiIiIiIiAGyOiIjoASKTyfDFF1/c97lERDQ5sDkiIiJJFBUVQSaTQSaTQaFQYMaMGdi4cSNGRkZ8dswrV65g+fLl930uERFNDsFSByAiogdXbm4uamtr8ffff6OpqQlGoxEhISF45513xsyz2+1QKBT/9/HUarVP5hIR0eTAlSMiIpJMaGgo1Go1kpKS8PLLLyM7OxsNDQ0oKipCQUEBtmzZgoSEBMycORMA8PPPP6OwsBDR0dGIiYlBfn4+bDbbmH1+8skn0Gq1CA0NhUajQWlpqeu1f98qZ7fbUVpaCo1GA6VSiaSkJGzbts3tXADo6urCkiVLEBYWhqlTp6KkpAQ3b950vX47c2VlJTQaDaZOnQqj0QiHw3H/3zgiIvIJNkdERBQwwsLCYLfbAQBmsxlWqxWnT59GY2MjHA4HcnJyoFKpcObMGbS1tSEyMhK5ubmubaqrq2E0GlFSUoKuri40NDRgxowZbo+1c+dONDQ04OjRo7BarThw4ACmT5/udu7Q0BBycnIwZcoUfP/99zh27BhaWlrGNF4AYLFY0NvbC4vFgv3796Ourg51dXX37f0hIiLf4m11REQkOSEEzGYzmpubsW7dOvz++++IiIhATU2N63a6zz77DE6nEzU1NZDJZACA2tpaREdHo7W1FcuWLcPmzZvx+uuv45VXXnHtOz093e0xL1++jEceeQSLFi2CTCZDUlLSuPkOHjyI4eFhfPrpp4iIiAAAVFVVYcWKFXj//fcRHx8PAJgyZQqqqqogl8sxa9Ys5OXlwWw244UXXrgv7xMREfkWV46IiEgyjY2NiIyMhFKpxPLly6HT6VBeXg4AmD179pjvGf3www/o6emBSqVCZGQkIiMjERMTg+HhYfT29uLatWv47bffsHTp0ns6dlFRETo7OzFz5kysX78ep06dGndud3c35syZ42qMACAzMxNOpxNWq9U1ptVqIZfLXc81Gg2uXbt2r28HERFJjCtHREQkmaysLFRXV0OhUCAhIQHBwf/8Wfp3IwIAN2/eRFpaGg4cOHDXfh566CEEBXn2/765c+eiv78fX375JVpaWlBYWIjs7GzU19d7dzIAQkJCxjyXyWRwOp1e74+IiPyLzREREUkmIiJi3O8E3Wnu3Lk4cuQI4uLiEBUV5XbO9OnTYTabkZWVdU/7jIqKgk6ng06nw8qVK5Gbm4sbN24gJiZmzLzU1FTU1dVhaGjI1bS1tbUhKCjI9WMRREQ08fG2OiIimhBWr16N2NhY5Ofn48yZM+jv70drayvWr1+PX375BQBQXl6ODz74ADt37sSlS5dw7tw57Nq1y+3+duzYgUOHDuHChQu4ePEijh07BrVajejoaLfHViqVMBgMOH/+PCwWC9atWwe9Xu/6vhEREU18bI6IiGhCCA8Px9dff41p06bhueeeQ2pqKoqLizE8POxaSTIYDPjwww+xZ88eaLVaPPPMM7h06ZLb/alUKmzfvh3z5s1Deno6bDYbmpqa3N6eFx4ejubmZty4cQPp6elYuXIlli5diqqqKp+eMxER+ZdMCCGkDkFERERERCQ1rhwRERERERGBzREREREREREANkdEREREREQA2BwREREREREBYHNEREREREQEgM0RERERERERADZHREREREREANgcERERERERAWBzREREREREBIDNEREREREREQA2R0RERERERADYHBEREREREQEA/geUVz5iqpVhUgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gpdsFyp64DhY"
   },
   "source": [
    "看起来精确率相对较高，但是召回率和 ROC 曲线下方面积 (AUC) 可能并没有您期望的那么高。当试图同时最大限度地提高精确率和召回率时，分类器通常会面临挑战，在处理不平衡数据集时尤其如此。请务必根据您所关心的问题来考虑不同类型错误的代价。在此示例中，假负例（漏掉欺诈交易）可能造成财务损失，而假正例（将交易错误地标记为欺诈）则可能降低用户满意度。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cveQoiMyGQCo"
   },
   "source": [
    "## 类权重"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ePGp6GUE1WfH"
   },
   "source": [
    "### 计算类权重\n",
    "\n",
    "我们的目标是识别欺诈交易，但您没有很多可以使用的此类正样本，因此您希望分类器提高可用的少数样本的权重。为此，您可以使用参数将 Keras 权重传递给每个类。这些权重将使模型“更加关注”来自代表不足的类的样本。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:19.250140Z",
     "iopub.status.busy": "2023-11-08T01:17:19.249514Z",
     "iopub.status.idle": "2023-11-08T01:17:19.254809Z",
     "shell.execute_reply": "2023-11-08T01:17:19.254055Z"
    },
    "id": "qjGWErngGny7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weight for class 0: 0.50\n",
      "Weight for class 1: 289.44\n"
     ]
    }
   ],
   "source": [
    "# Scaling by total/2 helps keep the loss to a similar magnitude.\n",
    "# The sum of the weights of all examples stays the same.\n",
    "weight_for_0 = (1 / neg) * (total / 2.0)\n",
    "weight_for_1 = (1 / pos) * (total / 2.0)\n",
    "\n",
    "class_weight = {0: weight_for_0, 1: weight_for_1}\n",
    "\n",
    "print('Weight for class 0: {:.2f}'.format(weight_for_0))\n",
    "print('Weight for class 1: {:.2f}'.format(weight_for_1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Mk1OOE2ZSHzy"
   },
   "source": [
    "### 使用类权重训练模型\n",
    "\n",
    "现在，尝试使用类权重对模型进行重新训练和评估，以了解其对预测的影响。\n",
    "\n",
    "注：使用 `class_weights` 会改变损失范围。这可能会影响训练的稳定性，具体取决于优化器。步长取决于梯度大小的优化器（如 `optimizers.SGD`）可能会失效。此处使用的优化器（`optimizers.Adam`）不受缩放更改的影响。还要注意，由于加权，两个模型之间的总损失不具可比性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:19.258593Z",
     "iopub.status.busy": "2023-11-08T01:17:19.258031Z",
     "iopub.status.idle": "2023-11-08T01:17:32.874777Z",
     "shell.execute_reply": "2023-11-08T01:17:32.873982Z"
    },
    "id": "UJ589fn8ST3x"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 2:15 - loss: 2.7137 - tp: 84.0000 - fp: 12.0000 - tn: 58888.0000 - fn: 26.0000 - accuracy: 0.9994 - precision: 0.8750 - recall: 0.7636 - auc: 0.9270 - prc: 0.8045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 5.3623 - tp: 86.0000 - fp: 12.0000 - tn: 83414.0000 - fn: 74.0000 - accuracy: 0.9990 - precision: 0.8776 - recall: 0.5375 - auc: 0.8172 - prc: 0.5830  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 4.7718 - tp: 90.0000 - fp: 12.0000 - tn: 107944.0000 - fn: 116.0000 - accuracy: 0.9988 - precision: 0.8824 - recall: 0.4369 - auc: 0.7838 - prc: 0.5056"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 4.1223 - tp: 93.0000 - fp: 13.0000 - tn: 132484.0000 - fn: 148.0000 - accuracy: 0.9988 - precision: 0.8774 - recall: 0.3859 - auc: 0.7641 - prc: 0.4585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 3.8363 - tp: 98.0000 - fp: 18.0000 - tn: 159060.0000 - fn: 186.0000 - accuracy: 0.9987 - precision: 0.8448 - recall: 0.3451 - auc: 0.7578 - prc: 0.3992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 3.7153 - tp: 107.0000 - fp: 19.0000 - tn: 183593.0000 - fn: 219.0000 - accuracy: 0.9987 - precision: 0.8492 - recall: 0.3282 - auc: 0.7462 - prc: 0.3745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 3.5262 - tp: 115.0000 - fp: 24.0000 - tn: 210172.0000 - fn: 251.0000 - accuracy: 0.9987 - precision: 0.8273 - recall: 0.3142 - auc: 0.7370 - prc: 0.3462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "88/90 [============================>.] - ETA: 0s - loss: 3.4695 - tp: 126.0000 - fp: 27.0000 - tn: 236739.0000 - fn: 294.0000 - accuracy: 0.9986 - precision: 0.8235 - recall: 0.3000 - auc: 0.7321 - prc: 0.3264"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 3s 12ms/step - loss: 3.4540 - tp: 127.0000 - fp: 28.0000 - tn: 238787.0000 - fn: 296.0000 - accuracy: 0.9986 - precision: 0.8194 - recall: 0.3002 - auc: 0.7327 - prc: 0.3224 - val_loss: 0.0070 - val_tp: 9.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 60.0000 - val_accuracy: 0.9986 - val_precision: 0.6000 - val_recall: 0.1304 - val_auc: 0.8538 - val_prc: 0.4746\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 1.5991 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 0.0000e+00 - recall: 0.0000e+00 - auc: 0.7378 - prc: 0.5010"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 2.7107 - tp: 18.0000 - fp: 3.0000 - tn: 26569.0000 - fn: 34.0000 - accuracy: 0.9986 - precision: 0.8571 - recall: 0.3462 - auc: 0.7342 - prc: 0.3242             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 2.4747 - tp: 32.0000 - fp: 8.0000 - tn: 51099.0000 - fn: 61.0000 - accuracy: 0.9987 - precision: 0.8000 - recall: 0.3441 - auc: 0.7248 - prc: 0.2976"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 2.4512 - tp: 52.0000 - fp: 11.0000 - tn: 75616.0000 - fn: 97.0000 - accuracy: 0.9986 - precision: 0.8254 - recall: 0.3490 - auc: 0.7516 - prc: 0.3397"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 2.1021 - tp: 58.0000 - fp: 18.0000 - tn: 100162.0000 - fn: 114.0000 - accuracy: 0.9987 - precision: 0.7632 - recall: 0.3372 - auc: 0.7557 - prc: 0.3273"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 2.0668 - tp: 69.0000 - fp: 28.0000 - tn: 124683.0000 - fn: 148.0000 - accuracy: 0.9986 - precision: 0.7113 - recall: 0.3180 - auc: 0.7685 - prc: 0.3197"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "73/90 [=======================>......] - ETA: 0s - loss: 1.9772 - tp: 86.0000 - fp: 35.0000 - tn: 149208.0000 - fn: 175.0000 - accuracy: 0.9986 - precision: 0.7107 - recall: 0.3295 - auc: 0.7871 - prc: 0.3406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "85/90 [===========================>..] - ETA: 0s - loss: 1.8861 - tp: 97.0000 - fp: 43.0000 - tn: 173742.0000 - fn: 198.0000 - accuracy: 0.9986 - precision: 0.6929 - recall: 0.3288 - auc: 0.7923 - prc: 0.3390"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 1.8967 - tp: 106.0000 - fp: 48.0000 - tn: 181912.0000 - fn: 210.0000 - accuracy: 0.9986 - precision: 0.6883 - recall: 0.3354 - auc: 0.7954 - prc: 0.3507 - val_loss: 0.0049 - val_tp: 48.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 21.0000 - val_accuracy: 0.9994 - val_precision: 0.8889 - val_recall: 0.6957 - val_auc: 0.9396 - val_prc: 0.6825\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.5117 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 0.9934 - prc: 0.5261"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.9296 - tp: 25.0000 - fp: 17.0000 - tn: 28611.0000 - fn: 19.0000 - accuracy: 0.9987 - precision: 0.5952 - recall: 0.5682 - auc: 0.8710 - prc: 0.5079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 1.1121 - tp: 53.0000 - fp: 33.0000 - tn: 55166.0000 - fn: 44.0000 - accuracy: 0.9986 - precision: 0.6163 - recall: 0.5464 - auc: 0.8811 - prc: 0.5141"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 1.1124 - tp: 83.0000 - fp: 51.0000 - tn: 79675.0000 - fn: 63.0000 - accuracy: 0.9986 - precision: 0.6194 - recall: 0.5685 - auc: 0.8889 - prc: 0.5438"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 1.1711 - tp: 97.0000 - fp: 64.0000 - tn: 104199.0000 - fn: 88.0000 - accuracy: 0.9985 - precision: 0.6025 - recall: 0.5243 - auc: 0.8779 - prc: 0.4960"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 1.1909 - tp: 122.0000 - fp: 78.0000 - tn: 128714.0000 - fn: 110.0000 - accuracy: 0.9985 - precision: 0.6100 - recall: 0.5259 - auc: 0.8793 - prc: 0.4969"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 1.2125 - tp: 143.0000 - fp: 104.0000 - tn: 153224.0000 - fn: 129.0000 - accuracy: 0.9985 - precision: 0.5789 - recall: 0.5257 - auc: 0.8709 - prc: 0.4865"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 1.1980 - tp: 162.0000 - fp: 128.0000 - tn: 177739.0000 - fn: 147.0000 - accuracy: 0.9985 - precision: 0.5586 - recall: 0.5243 - auc: 0.8653 - prc: 0.4703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 1.2148 - tp: 165.0000 - fp: 131.0000 - tn: 181829.0000 - fn: 151.0000 - accuracy: 0.9985 - precision: 0.5574 - recall: 0.5222 - auc: 0.8611 - prc: 0.4673 - val_loss: 0.0056 - val_tp: 53.0000 - val_fp: 11.0000 - val_tn: 45489.0000 - val_fn: 16.0000 - val_accuracy: 0.9994 - val_precision: 0.8281 - val_recall: 0.7681 - val_auc: 0.9592 - val_prc: 0.7340\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 1.7880 - tp: 4.0000 - fp: 3.0000 - tn: 2039.0000 - fn: 2.0000 - accuracy: 0.9976 - precision: 0.5714 - recall: 0.6667 - auc: 0.8103 - prc: 0.6684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.6351 - tp: 23.0000 - fp: 35.0000 - tn: 26550.0000 - fn: 16.0000 - accuracy: 0.9981 - precision: 0.3966 - recall: 0.5897 - auc: 0.9207 - prc: 0.4770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 1.0462 - tp: 50.0000 - fp: 77.0000 - tn: 51033.0000 - fn: 40.0000 - accuracy: 0.9977 - precision: 0.3937 - recall: 0.5556 - auc: 0.8678 - prc: 0.5026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 1.0181 - tp: 70.0000 - fp: 129.0000 - tn: 75519.0000 - fn: 58.0000 - accuracy: 0.9975 - precision: 0.3518 - recall: 0.5469 - auc: 0.8731 - prc: 0.4670"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.9686 - tp: 94.0000 - fp: 167.0000 - tn: 100019.0000 - fn: 72.0000 - accuracy: 0.9976 - precision: 0.3602 - recall: 0.5663 - auc: 0.8702 - prc: 0.4797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 0.9694 - tp: 119.0000 - fp: 218.0000 - tn: 124502.0000 - fn: 89.0000 - accuracy: 0.9975 - precision: 0.3531 - recall: 0.5721 - auc: 0.8752 - prc: 0.4896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "73/90 [=======================>......] - ETA: 0s - loss: 0.9561 - tp: 147.0000 - fp: 273.0000 - tn: 148980.0000 - fn: 104.0000 - accuracy: 0.9975 - precision: 0.3500 - recall: 0.5857 - auc: 0.8746 - prc: 0.4771"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "86/90 [===========================>..] - ETA: 0s - loss: 1.0020 - tp: 176.0000 - fp: 337.0000 - tn: 175486.0000 - fn: 129.0000 - accuracy: 0.9974 - precision: 0.3431 - recall: 0.5770 - auc: 0.8700 - prc: 0.4737"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.9954 - tp: 184.0000 - fp: 354.0000 - tn: 181606.0000 - fn: 132.0000 - accuracy: 0.9973 - precision: 0.3420 - recall: 0.5823 - auc: 0.8707 - prc: 0.4738 - val_loss: 0.0071 - val_tp: 58.0000 - val_fp: 15.0000 - val_tn: 45485.0000 - val_fn: 11.0000 - val_accuracy: 0.9994 - val_precision: 0.7945 - val_recall: 0.8406 - val_auc: 0.9857 - val_prc: 0.7529\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0052 - tp: 3.0000 - fp: 2.0000 - tn: 2043.0000 - fn: 0.0000e+00 - accuracy: 0.9990 - precision: 0.6000 - recall: 1.0000 - auc: 0.9998 - prc: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.9010 - tp: 27.0000 - fp: 67.0000 - tn: 28559.0000 - fn: 19.0000 - accuracy: 0.9970 - precision: 0.2872 - recall: 0.5870 - auc: 0.8756 - prc: 0.4410"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.7859 - tp: 56.0000 - fp: 133.0000 - tn: 53027.0000 - fn: 32.0000 - accuracy: 0.9969 - precision: 0.2963 - recall: 0.6364 - auc: 0.8958 - prc: 0.4770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.7561 - tp: 89.0000 - fp: 207.0000 - tn: 77484.0000 - fn: 44.0000 - accuracy: 0.9968 - precision: 0.3007 - recall: 0.6692 - auc: 0.9014 - prc: 0.5053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.8124 - tp: 114.0000 - fp: 294.0000 - tn: 101930.0000 - fn: 62.0000 - accuracy: 0.9965 - precision: 0.2794 - recall: 0.6477 - auc: 0.8895 - prc: 0.4965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.8466 - tp: 132.0000 - fp: 393.0000 - tn: 126374.0000 - fn: 77.0000 - accuracy: 0.9963 - precision: 0.2514 - recall: 0.6316 - auc: 0.8742 - prc: 0.4795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.8089 - tp: 170.0000 - fp: 521.0000 - tn: 152820.0000 - fn: 89.0000 - accuracy: 0.9960 - precision: 0.2460 - recall: 0.6564 - auc: 0.8812 - prc: 0.4928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.8376 - tp: 205.0000 - fp: 634.0000 - tn: 177233.0000 - fn: 104.0000 - accuracy: 0.9959 - precision: 0.2443 - recall: 0.6634 - auc: 0.8824 - prc: 0.4857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.8191 - tp: 212.0000 - fp: 650.0000 - tn: 181310.0000 - fn: 104.0000 - accuracy: 0.9959 - precision: 0.2459 - recall: 0.6709 - auc: 0.8850 - prc: 0.4946 - val_loss: 0.0097 - val_tp: 59.0000 - val_fp: 29.0000 - val_tn: 45471.0000 - val_fn: 10.0000 - val_accuracy: 0.9991 - val_precision: 0.6705 - val_recall: 0.8551 - val_auc: 0.9918 - val_prc: 0.7607\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0103 - tp: 4.0000 - fp: 12.0000 - tn: 2032.0000 - fn: 0.0000e+00 - accuracy: 0.9941 - precision: 0.2500 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.4378 - tp: 38.0000 - fp: 150.0000 - tn: 28474.0000 - fn: 10.0000 - accuracy: 0.9944 - precision: 0.2021 - recall: 0.7917 - auc: 0.9410 - prc: 0.5805"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.6826 - tp: 71.0000 - fp: 285.0000 - tn: 52865.0000 - fn: 27.0000 - accuracy: 0.9941 - precision: 0.1994 - recall: 0.7245 - auc: 0.9056 - prc: 0.4827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.6308 - tp: 99.0000 - fp: 415.0000 - tn: 77272.0000 - fn: 38.0000 - accuracy: 0.9942 - precision: 0.1926 - recall: 0.7226 - auc: 0.9118 - prc: 0.4681"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.6573 - tp: 129.0000 - fp: 590.0000 - tn: 103679.0000 - fn: 50.0000 - accuracy: 0.9939 - precision: 0.1794 - recall: 0.7207 - auc: 0.9057 - prc: 0.4666"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.7253 - tp: 157.0000 - fp: 767.0000 - tn: 130079.0000 - fn: 69.0000 - accuracy: 0.9936 - precision: 0.1699 - recall: 0.6947 - auc: 0.8923 - prc: 0.4366"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.6994 - tp: 195.0000 - fp: 958.0000 - tn: 156464.0000 - fn: 79.0000 - accuracy: 0.9934 - precision: 0.1691 - recall: 0.7117 - auc: 0.8964 - prc: 0.4364"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.6886 - tp: 225.0000 - fp: 1145.0000 - tn: 180815.0000 - fn: 91.0000 - accuracy: 0.9932 - precision: 0.1642 - recall: 0.7120 - auc: 0.8986 - prc: 0.4293"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.6886 - tp: 225.0000 - fp: 1145.0000 - tn: 180815.0000 - fn: 91.0000 - accuracy: 0.9932 - precision: 0.1642 - recall: 0.7120 - auc: 0.8986 - prc: 0.4293 - val_loss: 0.0142 - val_tp: 59.0000 - val_fp: 89.0000 - val_tn: 45411.0000 - val_fn: 10.0000 - val_accuracy: 0.9978 - val_precision: 0.3986 - val_recall: 0.8551 - val_auc: 0.9930 - val_prc: 0.7548\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.6103 - tp: 4.0000 - fp: 14.0000 - tn: 2029.0000 - fn: 1.0000 - accuracy: 0.9927 - precision: 0.2222 - recall: 0.8000 - auc: 0.9713 - prc: 0.4602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.7032 - tp: 33.0000 - fp: 215.0000 - tn: 26363.0000 - fn: 13.0000 - accuracy: 0.9914 - precision: 0.1331 - recall: 0.7174 - auc: 0.9057 - prc: 0.3429"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.5990 - tp: 56.0000 - fp: 437.0000 - tn: 50686.0000 - fn: 21.0000 - accuracy: 0.9911 - precision: 0.1136 - recall: 0.7273 - auc: 0.9027 - prc: 0.3124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.6570 - tp: 85.0000 - fp: 673.0000 - tn: 74986.0000 - fn: 32.0000 - accuracy: 0.9907 - precision: 0.1121 - recall: 0.7265 - auc: 0.8818 - prc: 0.3485"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.6247 - tp: 129.0000 - fp: 853.0000 - tn: 99329.0000 - fn: 41.0000 - accuracy: 0.9911 - precision: 0.1314 - recall: 0.7588 - auc: 0.9008 - prc: 0.4035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.5939 - tp: 164.0000 - fp: 1090.0000 - tn: 125670.0000 - fn: 52.0000 - accuracy: 0.9910 - precision: 0.1308 - recall: 0.7593 - auc: 0.9072 - prc: 0.4250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "74/90 [=======================>......] - ETA: 0s - loss: 0.5975 - tp: 201.0000 - fp: 1340.0000 - tn: 149949.0000 - fn: 62.0000 - accuracy: 0.9907 - precision: 0.1304 - recall: 0.7643 - auc: 0.9102 - prc: 0.4184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "86/90 [===========================>..] - ETA: 0s - loss: 0.6025 - tp: 230.0000 - fp: 1609.0000 - tn: 174216.0000 - fn: 73.0000 - accuracy: 0.9905 - precision: 0.1251 - recall: 0.7591 - auc: 0.9083 - prc: 0.3786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.6061 - tp: 240.0000 - fp: 1686.0000 - tn: 180274.0000 - fn: 76.0000 - accuracy: 0.9903 - precision: 0.1246 - recall: 0.7595 - auc: 0.9086 - prc: 0.3771 - val_loss: 0.0198 - val_tp: 60.0000 - val_fp: 182.0000 - val_tn: 45318.0000 - val_fn: 9.0000 - val_accuracy: 0.9958 - val_precision: 0.2479 - val_recall: 0.8696 - val_auc: 0.9946 - val_prc: 0.7211\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.4736 - tp: 4.0000 - fp: 29.0000 - tn: 2014.0000 - fn: 1.0000 - accuracy: 0.9854 - precision: 0.1212 - recall: 0.8000 - auc: 0.9851 - prc: 0.5392"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.5087 - tp: 31.0000 - fp: 302.0000 - tn: 26281.0000 - fn: 10.0000 - accuracy: 0.9883 - precision: 0.0931 - recall: 0.7561 - auc: 0.9078 - prc: 0.2812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.5006 - tp: 70.0000 - fp: 575.0000 - tn: 50536.0000 - fn: 19.0000 - accuracy: 0.9884 - precision: 0.1085 - recall: 0.7865 - auc: 0.9250 - prc: 0.3489"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.5707 - tp: 94.0000 - fp: 883.0000 - tn: 74765.0000 - fn: 34.0000 - accuracy: 0.9879 - precision: 0.0962 - recall: 0.7344 - auc: 0.9216 - prc: 0.3200"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.6151 - tp: 117.0000 - fp: 1192.0000 - tn: 98995.0000 - fn: 48.0000 - accuracy: 0.9876 - precision: 0.0894 - recall: 0.7091 - auc: 0.9113 - prc: 0.2967"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 0.6056 - tp: 146.0000 - fp: 1499.0000 - tn: 123224.0000 - fn: 59.0000 - accuracy: 0.9875 - precision: 0.0888 - recall: 0.7122 - auc: 0.9100 - prc: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "73/90 [=======================>......] - ETA: 0s - loss: 0.5961 - tp: 182.0000 - fp: 1831.0000 - tn: 147423.0000 - fn: 68.0000 - accuracy: 0.9873 - precision: 0.0904 - recall: 0.7280 - auc: 0.9108 - prc: 0.3199"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "85/90 [===========================>..] - ETA: 0s - loss: 0.6089 - tp: 218.0000 - fp: 2163.0000 - tn: 171620.0000 - fn: 79.0000 - accuracy: 0.9871 - precision: 0.0916 - recall: 0.7340 - auc: 0.9067 - prc: 0.3197"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.6127 - tp: 233.0000 - fp: 2287.0000 - tn: 179673.0000 - fn: 83.0000 - accuracy: 0.9870 - precision: 0.0925 - recall: 0.7373 - auc: 0.9071 - prc: 0.3235 - val_loss: 0.0276 - val_tp: 64.0000 - val_fp: 340.0000 - val_tn: 45160.0000 - val_fn: 5.0000 - val_accuracy: 0.9924 - val_precision: 0.1584 - val_recall: 0.9275 - val_auc: 0.9953 - val_prc: 0.6965\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 1.5614 - tp: 2.0000 - fp: 31.0000 - tn: 2013.0000 - fn: 2.0000 - accuracy: 0.9839 - precision: 0.0606 - recall: 0.5000 - auc: 0.7331 - prc: 0.1682"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.7870 - tp: 42.0000 - fp: 395.0000 - tn: 26169.0000 - fn: 18.0000 - accuracy: 0.9845 - precision: 0.0961 - recall: 0.7000 - auc: 0.9109 - prc: 0.3395"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.7410 - tp: 77.0000 - fp: 839.0000 - tn: 52299.0000 - fn: 33.0000 - accuracy: 0.9836 - precision: 0.0841 - recall: 0.7000 - auc: 0.9096 - prc: 0.3218"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.6296 - tp: 106.0000 - fp: 1221.0000 - tn: 76454.0000 - fn: 43.0000 - accuracy: 0.9838 - precision: 0.0799 - recall: 0.7114 - auc: 0.9187 - prc: 0.3113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.5557 - tp: 142.0000 - fp: 1619.0000 - tn: 100590.0000 - fn: 49.0000 - accuracy: 0.9837 - precision: 0.0806 - recall: 0.7435 - auc: 0.9256 - prc: 0.3232"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.5025 - tp: 178.0000 - fp: 2093.0000 - tn: 124649.0000 - fn: 56.0000 - accuracy: 0.9831 - precision: 0.0784 - recall: 0.7607 - auc: 0.9343 - prc: 0.3029"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "74/90 [=======================>......] - ETA: 0s - loss: 0.5020 - tp: 213.0000 - fp: 2525.0000 - tn: 148747.0000 - fn: 67.0000 - accuracy: 0.9829 - precision: 0.0778 - recall: 0.7607 - auc: 0.9333 - prc: 0.2921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "86/90 [===========================>..] - ETA: 0s - loss: 0.4678 - tp: 238.0000 - fp: 3004.0000 - tn: 172815.0000 - fn: 71.0000 - accuracy: 0.9825 - precision: 0.0734 - recall: 0.7702 - auc: 0.9344 - prc: 0.2783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.4657 - tp: 244.0000 - fp: 3136.0000 - tn: 178824.0000 - fn: 72.0000 - accuracy: 0.9824 - precision: 0.0722 - recall: 0.7722 - auc: 0.9334 - prc: 0.2770 - val_loss: 0.0385 - val_tp: 64.0000 - val_fp: 514.0000 - val_tn: 44986.0000 - val_fn: 5.0000 - val_accuracy: 0.9886 - val_precision: 0.1107 - val_recall: 0.9275 - val_auc: 0.9953 - val_prc: 0.6873\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.2612 - tp: 8.0000 - fp: 33.0000 - tn: 2006.0000 - fn: 1.0000 - accuracy: 0.9834 - precision: 0.1951 - recall: 0.8889 - auc: 0.9950 - prc: 0.6468"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.4458 - tp: 42.0000 - fp: 541.0000 - tn: 26031.0000 - fn: 10.0000 - accuracy: 0.9793 - precision: 0.0720 - recall: 0.8077 - auc: 0.9461 - prc: 0.2932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.6278 - tp: 72.0000 - fp: 1058.0000 - tn: 50045.0000 - fn: 25.0000 - accuracy: 0.9788 - precision: 0.0637 - recall: 0.7423 - auc: 0.9113 - prc: 0.2388"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.5405 - tp: 107.0000 - fp: 1618.0000 - tn: 76068.0000 - fn: 31.0000 - accuracy: 0.9788 - precision: 0.0620 - recall: 0.7754 - auc: 0.9156 - prc: 0.2322"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.5122 - tp: 143.0000 - fp: 2193.0000 - tn: 102071.0000 - fn: 41.0000 - accuracy: 0.9786 - precision: 0.0612 - recall: 0.7772 - auc: 0.9217 - prc: 0.2272"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.5250 - tp: 180.0000 - fp: 2802.0000 - tn: 128035.0000 - fn: 55.0000 - accuracy: 0.9782 - precision: 0.0604 - recall: 0.7660 - auc: 0.9237 - prc: 0.2161"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.4742 - tp: 211.0000 - fp: 3398.0000 - tn: 151981.0000 - fn: 58.0000 - accuracy: 0.9778 - precision: 0.0585 - recall: 0.7844 - auc: 0.9291 - prc: 0.2095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.4505 - tp: 254.0000 - fp: 4029.0000 - tn: 177927.0000 - fn: 62.0000 - accuracy: 0.9776 - precision: 0.0593 - recall: 0.8038 - auc: 0.9320 - prc: 0.2187"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.4505 - tp: 254.0000 - fp: 4030.0000 - tn: 177930.0000 - fn: 62.0000 - accuracy: 0.9776 - precision: 0.0593 - recall: 0.8038 - auc: 0.9320 - prc: 0.2187 - val_loss: 0.0484 - val_tp: 64.0000 - val_fp: 642.0000 - val_tn: 44858.0000 - val_fn: 5.0000 - val_accuracy: 0.9858 - val_precision: 0.0907 - val_recall: 0.9275 - val_auc: 0.9953 - val_prc: 0.6514\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.1446 - tp: 4.0000 - fp: 47.0000 - tn: 1996.0000 - fn: 1.0000 - accuracy: 0.9766 - precision: 0.0784 - recall: 0.8000 - auc: 0.9940 - prc: 0.3084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.3950 - tp: 43.0000 - fp: 697.0000 - tn: 27923.0000 - fn: 9.0000 - accuracy: 0.9754 - precision: 0.0581 - recall: 0.8269 - auc: 0.9292 - prc: 0.2378"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.5501 - tp: 81.0000 - fp: 1281.0000 - tn: 51867.0000 - fn: 19.0000 - accuracy: 0.9756 - precision: 0.0595 - recall: 0.8100 - auc: 0.8969 - prc: 0.2527"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.5271 - tp: 116.0000 - fp: 1911.0000 - tn: 77815.0000 - fn: 30.0000 - accuracy: 0.9757 - precision: 0.0572 - recall: 0.7945 - auc: 0.9070 - prc: 0.2301"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.4725 - tp: 144.0000 - fp: 2544.0000 - tn: 101725.0000 - fn: 35.0000 - accuracy: 0.9753 - precision: 0.0536 - recall: 0.8045 - auc: 0.9144 - prc: 0.2164"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.4491 - tp: 181.0000 - fp: 3238.0000 - tn: 127608.0000 - fn: 45.0000 - accuracy: 0.9750 - precision: 0.0529 - recall: 0.8009 - auc: 0.9217 - prc: 0.2123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.4514 - tp: 219.0000 - fp: 3947.0000 - tn: 153475.0000 - fn: 55.0000 - accuracy: 0.9746 - precision: 0.0526 - recall: 0.7993 - auc: 0.9226 - prc: 0.2169"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.4498 - tp: 252.0000 - fp: 4605.0000 - tn: 177355.0000 - fn: 64.0000 - accuracy: 0.9744 - precision: 0.0519 - recall: 0.7975 - auc: 0.9242 - prc: 0.2122"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.4498 - tp: 252.0000 - fp: 4605.0000 - tn: 177355.0000 - fn: 64.0000 - accuracy: 0.9744 - precision: 0.0519 - recall: 0.7975 - auc: 0.9242 - prc: 0.2122 - val_loss: 0.0548 - val_tp: 64.0000 - val_fp: 694.0000 - val_tn: 44806.0000 - val_fn: 5.0000 - val_accuracy: 0.9847 - val_precision: 0.0844 - val_recall: 0.9275 - val_auc: 0.9953 - val_prc: 0.6065\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0521 - tp: 1.0000 - fp: 51.0000 - tn: 1996.0000 - fn: 0.0000e+00 - accuracy: 0.9751 - precision: 0.0192 - recall: 1.0000 - auc: 0.9971 - prc: 0.0722"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.3071 - tp: 37.0000 - fp: 668.0000 - tn: 25914.0000 - fn: 5.0000 - accuracy: 0.9747 - precision: 0.0525 - recall: 0.8810 - auc: 0.9388 - prc: 0.2606 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.4531 - tp: 75.0000 - fp: 1336.0000 - tn: 49771.0000 - fn: 18.0000 - accuracy: 0.9736 - precision: 0.0532 - recall: 0.8065 - auc: 0.9299 - prc: 0.2275"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.4435 - tp: 104.0000 - fp: 2037.0000 - tn: 73610.0000 - fn: 25.0000 - accuracy: 0.9728 - precision: 0.0486 - recall: 0.8062 - auc: 0.9224 - prc: 0.2135"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.4117 - tp: 142.0000 - fp: 2743.0000 - tn: 97436.0000 - fn: 31.0000 - accuracy: 0.9724 - precision: 0.0492 - recall: 0.8208 - auc: 0.9285 - prc: 0.2054"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 0.4089 - tp: 174.0000 - fp: 3490.0000 - tn: 121227.0000 - fn: 37.0000 - accuracy: 0.9718 - precision: 0.0475 - recall: 0.8246 - auc: 0.9248 - prc: 0.1937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "73/90 [=======================>......] - ETA: 0s - loss: 0.3956 - tp: 204.0000 - fp: 4227.0000 - tn: 145029.0000 - fn: 44.0000 - accuracy: 0.9714 - precision: 0.0460 - recall: 0.8226 - auc: 0.9273 - prc: 0.1856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "85/90 [===========================>..] - ETA: 0s - loss: 0.4070 - tp: 244.0000 - fp: 4934.0000 - tn: 168848.0000 - fn: 54.0000 - accuracy: 0.9713 - precision: 0.0471 - recall: 0.8188 - auc: 0.9263 - prc: 0.1927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.4053 - tp: 260.0000 - fp: 5182.0000 - tn: 176778.0000 - fn: 56.0000 - accuracy: 0.9713 - precision: 0.0478 - recall: 0.8228 - auc: 0.9284 - prc: 0.1952 - val_loss: 0.0608 - val_tp: 64.0000 - val_fp: 767.0000 - val_tn: 44733.0000 - val_fn: 5.0000 - val_accuracy: 0.9831 - val_precision: 0.0770 - val_recall: 0.9275 - val_auc: 0.9953 - val_prc: 0.6025\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.9509 - tp: 3.0000 - fp: 47.0000 - tn: 1997.0000 - fn: 1.0000 - accuracy: 0.9766 - precision: 0.0600 - recall: 0.7500 - auc: 0.7945 - prc: 0.1143"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.5321 - tp: 39.0000 - fp: 780.0000 - tn: 25795.0000 - fn: 10.0000 - accuracy: 0.9703 - precision: 0.0476 - recall: 0.7959 - auc: 0.9173 - prc: 0.1550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.4396 - tp: 76.0000 - fp: 1571.0000 - tn: 49534.0000 - fn: 19.0000 - accuracy: 0.9689 - precision: 0.0461 - recall: 0.8000 - auc: 0.9402 - prc: 0.1880"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.3981 - tp: 120.0000 - fp: 2421.0000 - tn: 75255.0000 - fn: 28.0000 - accuracy: 0.9685 - precision: 0.0472 - recall: 0.8108 - auc: 0.9485 - prc: 0.2023"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.3315 - tp: 157.0000 - fp: 3234.0000 - tn: 98978.0000 - fn: 31.0000 - accuracy: 0.9681 - precision: 0.0463 - recall: 0.8351 - auc: 0.9576 - prc: 0.2089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.3056 - tp: 197.0000 - fp: 4081.0000 - tn: 122662.0000 - fn: 36.0000 - accuracy: 0.9676 - precision: 0.0460 - recall: 0.8455 - auc: 0.9619 - prc: 0.2130"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.2762 - tp: 223.0000 - fp: 4972.0000 - tn: 148367.0000 - fn: 38.0000 - accuracy: 0.9674 - precision: 0.0429 - recall: 0.8544 - auc: 0.9639 - prc: 0.1979"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.3241 - tp: 259.0000 - fp: 5823.0000 - tn: 172044.0000 - fn: 50.0000 - accuracy: 0.9670 - precision: 0.0426 - recall: 0.8382 - auc: 0.9550 - prc: 0.1930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3426 - tp: 263.0000 - fp: 5964.0000 - tn: 175996.0000 - fn: 53.0000 - accuracy: 0.9670 - precision: 0.0422 - recall: 0.8323 - auc: 0.9503 - prc: 0.1911 - val_loss: 0.0683 - val_tp: 64.0000 - val_fp: 849.0000 - val_tn: 44651.0000 - val_fn: 5.0000 - val_accuracy: 0.9813 - val_precision: 0.0701 - val_recall: 0.9275 - val_auc: 0.9950 - val_prc: 0.5961\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 1.9254 - tp: 4.0000 - fp: 81.0000 - tn: 1961.0000 - fn: 2.0000 - accuracy: 0.9595 - precision: 0.0471 - recall: 0.6667 - auc: 0.7235 - prc: 0.1445"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.3116 - tp: 42.0000 - fp: 913.0000 - tn: 25664.0000 - fn: 5.0000 - accuracy: 0.9655 - precision: 0.0440 - recall: 0.8936 - auc: 0.9485 - prc: 0.2244"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.3004 - tp: 79.0000 - fp: 1778.0000 - tn: 49334.0000 - fn: 9.0000 - accuracy: 0.9651 - precision: 0.0425 - recall: 0.8977 - auc: 0.9456 - prc: 0.2105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.3301 - tp: 111.0000 - fp: 2729.0000 - tn: 74966.0000 - fn: 18.0000 - accuracy: 0.9647 - precision: 0.0391 - recall: 0.8605 - auc: 0.9409 - prc: 0.1970"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.3755 - tp: 154.0000 - fp: 3713.0000 - tn: 100552.0000 - fn: 29.0000 - accuracy: 0.9642 - precision: 0.0398 - recall: 0.8415 - auc: 0.9352 - prc: 0.1918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.3472 - tp: 194.0000 - fp: 4595.0000 - tn: 126250.0000 - fn: 33.0000 - accuracy: 0.9647 - precision: 0.0405 - recall: 0.8546 - auc: 0.9417 - prc: 0.1939"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.3493 - tp: 231.0000 - fp: 5425.0000 - tn: 149952.0000 - fn: 40.0000 - accuracy: 0.9649 - precision: 0.0408 - recall: 0.8524 - auc: 0.9411 - prc: 0.1959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "88/90 [============================>.] - ETA: 0s - loss: 0.3660 - tp: 266.0000 - fp: 6282.0000 - tn: 173628.0000 - fn: 48.0000 - accuracy: 0.9649 - precision: 0.0406 - recall: 0.8471 - auc: 0.9361 - prc: 0.1909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3627 - tp: 268.0000 - fp: 6356.0000 - tn: 175604.0000 - fn: 48.0000 - accuracy: 0.9649 - precision: 0.0405 - recall: 0.8481 - auc: 0.9365 - prc: 0.1903 - val_loss: 0.0714 - val_tp: 64.0000 - val_fp: 880.0000 - val_tn: 44620.0000 - val_fn: 5.0000 - val_accuracy: 0.9806 - val_precision: 0.0678 - val_recall: 0.9275 - val_auc: 0.9951 - val_prc: 0.5914\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0666 - tp: 2.0000 - fp: 89.0000 - tn: 1957.0000 - fn: 0.0000e+00 - accuracy: 0.9565 - precision: 0.0220 - recall: 1.0000 - auc: 0.9988 - prc: 0.2857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.5102 - tp: 45.0000 - fp: 977.0000 - tn: 25591.0000 - fn: 11.0000 - accuracy: 0.9629 - precision: 0.0440 - recall: 0.8036 - auc: 0.9270 - prc: 0.2043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.3842 - tp: 88.0000 - fp: 1901.0000 - tn: 49196.0000 - fn: 15.0000 - accuracy: 0.9626 - precision: 0.0442 - recall: 0.8544 - auc: 0.9454 - prc: 0.2117"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.3434 - tp: 113.0000 - fp: 2802.0000 - tn: 72841.0000 - fn: 20.0000 - accuracy: 0.9628 - precision: 0.0388 - recall: 0.8496 - auc: 0.9451 - prc: 0.1947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "49/90 [===============>..............] - ETA: 0s - loss: 0.3346 - tp: 150.0000 - fp: 3707.0000 - tn: 96471.0000 - fn: 24.0000 - accuracy: 0.9628 - precision: 0.0389 - recall: 0.8621 - auc: 0.9452 - prc: 0.1933"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "61/90 [===================>..........] - ETA: 0s - loss: 0.3474 - tp: 191.0000 - fp: 4630.0000 - tn: 120074.0000 - fn: 33.0000 - accuracy: 0.9627 - precision: 0.0396 - recall: 0.8527 - auc: 0.9446 - prc: 0.1997"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "73/90 [=======================>......] - ETA: 0s - loss: 0.3452 - tp: 219.0000 - fp: 5524.0000 - tn: 143723.0000 - fn: 38.0000 - accuracy: 0.9628 - precision: 0.0381 - recall: 0.8521 - auc: 0.9412 - prc: 0.1959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "85/90 [===========================>..] - ETA: 0s - loss: 0.3333 - tp: 258.0000 - fp: 6435.0000 - tn: 167343.0000 - fn: 44.0000 - accuracy: 0.9628 - precision: 0.0385 - recall: 0.8543 - auc: 0.9461 - prc: 0.1996"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3306 - tp: 271.0000 - fp: 6756.0000 - tn: 175204.0000 - fn: 45.0000 - accuracy: 0.9627 - precision: 0.0386 - recall: 0.8576 - auc: 0.9458 - prc: 0.2015 - val_loss: 0.0741 - val_tp: 64.0000 - val_fp: 914.0000 - val_tn: 44586.0000 - val_fn: 5.0000 - val_accuracy: 0.9798 - val_precision: 0.0654 - val_recall: 0.9275 - val_auc: 0.9948 - val_prc: 0.5921\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0651 - tp: 3.0000 - fp: 78.0000 - tn: 1967.0000 - fn: 0.0000e+00 - accuracy: 0.9619 - precision: 0.0370 - recall: 1.0000 - auc: 0.9980 - prc: 0.2727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.1889 - tp: 41.0000 - fp: 1015.0000 - tn: 25565.0000 - fn: 3.0000 - accuracy: 0.9618 - precision: 0.0388 - recall: 0.9318 - auc: 0.9700 - prc: 0.2197"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.2483 - tp: 75.0000 - fp: 1885.0000 - tn: 49232.0000 - fn: 8.0000 - accuracy: 0.9630 - precision: 0.0383 - recall: 0.9036 - auc: 0.9548 - prc: 0.2035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.3091 - tp: 105.0000 - fp: 2876.0000 - tn: 74826.0000 - fn: 17.0000 - accuracy: 0.9628 - precision: 0.0352 - recall: 0.8607 - auc: 0.9438 - prc: 0.1671"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.2902 - tp: 151.0000 - fp: 3859.0000 - tn: 100417.0000 - fn: 21.0000 - accuracy: 0.9629 - precision: 0.0377 - recall: 0.8779 - auc: 0.9486 - prc: 0.1821"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.3535 - tp: 192.0000 - fp: 4843.0000 - tn: 126004.0000 - fn: 33.0000 - accuracy: 0.9628 - precision: 0.0381 - recall: 0.8533 - auc: 0.9342 - prc: 0.1768"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "76/90 [========================>.....] - ETA: 0s - loss: 0.3347 - tp: 227.0000 - fp: 5809.0000 - tn: 149572.0000 - fn: 40.0000 - accuracy: 0.9624 - precision: 0.0376 - recall: 0.8502 - auc: 0.9404 - prc: 0.1746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "89/90 [============================>.] - ETA: 0s - loss: 0.3222 - tp: 272.0000 - fp: 6837.0000 - tn: 175119.0000 - fn: 44.0000 - accuracy: 0.9622 - precision: 0.0383 - recall: 0.8608 - auc: 0.9446 - prc: 0.1837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3222 - tp: 272.0000 - fp: 6837.0000 - tn: 175123.0000 - fn: 44.0000 - accuracy: 0.9622 - precision: 0.0383 - recall: 0.8608 - auc: 0.9446 - prc: 0.1837 - val_loss: 0.0752 - val_tp: 65.0000 - val_fp: 923.0000 - val_tn: 44577.0000 - val_fn: 4.0000 - val_accuracy: 0.9797 - val_precision: 0.0658 - val_recall: 0.9420 - val_auc: 0.9947 - val_prc: 0.5894\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0693 - tp: 2.0000 - fp: 70.0000 - tn: 1976.0000 - fn: 0.0000e+00 - accuracy: 0.9658 - precision: 0.0278 - recall: 1.0000 - auc: 0.9988 - prc: 0.2857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.3282 - tp: 38.0000 - fp: 1070.0000 - tn: 27558.0000 - fn: 6.0000 - accuracy: 0.9625 - precision: 0.0343 - recall: 0.8636 - auc: 0.9278 - prc: 0.1893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.4098 - tp: 74.0000 - fp: 2166.0000 - tn: 53041.0000 - fn: 15.0000 - accuracy: 0.9606 - precision: 0.0330 - recall: 0.8315 - auc: 0.9103 - prc: 0.1693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.3891 - tp: 111.0000 - fp: 3104.0000 - tn: 76636.0000 - fn: 21.0000 - accuracy: 0.9609 - precision: 0.0345 - recall: 0.8409 - auc: 0.9204 - prc: 0.1717"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.3828 - tp: 166.0000 - fp: 4129.0000 - tn: 102171.0000 - fn: 30.0000 - accuracy: 0.9609 - precision: 0.0386 - recall: 0.8469 - auc: 0.9325 - prc: 0.1971"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "64/90 [====================>.........] - ETA: 0s - loss: 0.3478 - tp: 201.0000 - fp: 5091.0000 - tn: 125745.0000 - fn: 35.0000 - accuracy: 0.9609 - precision: 0.0380 - recall: 0.8517 - auc: 0.9389 - prc: 0.1954"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "77/90 [========================>.....] - ETA: 0s - loss: 0.3584 - tp: 237.0000 - fp: 6230.0000 - tn: 151185.0000 - fn: 44.0000 - accuracy: 0.9602 - precision: 0.0366 - recall: 0.8434 - auc: 0.9381 - prc: 0.1845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.3474 - tp: 267.0000 - fp: 7262.0000 - tn: 174698.0000 - fn: 49.0000 - accuracy: 0.9599 - precision: 0.0355 - recall: 0.8449 - auc: 0.9397 - prc: 0.1785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3474 - tp: 267.0000 - fp: 7262.0000 - tn: 174698.0000 - fn: 49.0000 - accuracy: 0.9599 - precision: 0.0355 - recall: 0.8449 - auc: 0.9397 - prc: 0.1785 - val_loss: 0.0808 - val_tp: 65.0000 - val_fp: 979.0000 - val_tn: 44521.0000 - val_fn: 4.0000 - val_accuracy: 0.9784 - val_precision: 0.0623 - val_recall: 0.9420 - val_auc: 0.9947 - val_prc: 0.5926\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.3719 - tp: 2.0000 - fp: 77.0000 - tn: 1968.0000 - fn: 1.0000 - accuracy: 0.9619 - precision: 0.0253 - recall: 0.6667 - auc: 0.9567 - prc: 0.0866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.1377 - tp: 41.0000 - fp: 1145.0000 - tn: 25436.0000 - fn: 2.0000 - accuracy: 0.9569 - precision: 0.0346 - recall: 0.9535 - auc: 0.9894 - prc: 0.1811"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.2345 - tp: 89.0000 - fp: 2133.0000 - tn: 51018.0000 - fn: 8.0000 - accuracy: 0.9598 - precision: 0.0401 - recall: 0.9175 - auc: 0.9640 - prc: 0.2127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.2839 - tp: 120.0000 - fp: 3228.0000 - tn: 76506.0000 - fn: 18.0000 - accuracy: 0.9594 - precision: 0.0358 - recall: 0.8696 - auc: 0.9549 - prc: 0.1726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "52/90 [================>.............] - ETA: 0s - loss: 0.3416 - tp: 149.0000 - fp: 4309.0000 - tn: 102009.0000 - fn: 29.0000 - accuracy: 0.9593 - precision: 0.0334 - recall: 0.8371 - auc: 0.9402 - prc: 0.1630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "65/90 [====================>.........] - ETA: 0s - loss: 0.3292 - tp: 183.0000 - fp: 5339.0000 - tn: 127564.0000 - fn: 34.0000 - accuracy: 0.9596 - precision: 0.0331 - recall: 0.8433 - auc: 0.9411 - prc: 0.1675"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "78/90 [=========================>....] - ETA: 0s - loss: 0.3488 - tp: 228.0000 - fp: 6446.0000 - tn: 153027.0000 - fn: 43.0000 - accuracy: 0.9594 - precision: 0.0342 - recall: 0.8413 - auc: 0.9377 - prc: 0.1723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - ETA: 0s - loss: 0.3525 - tp: 267.0000 - fp: 7350.0000 - tn: 174610.0000 - fn: 49.0000 - accuracy: 0.9594 - precision: 0.0351 - recall: 0.8449 - auc: 0.9373 - prc: 0.1762"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3525 - tp: 267.0000 - fp: 7350.0000 - tn: 174610.0000 - fn: 49.0000 - accuracy: 0.9594 - precision: 0.0351 - recall: 0.8449 - auc: 0.9373 - prc: 0.1762 - val_loss: 0.0806 - val_tp: 65.0000 - val_fp: 977.0000 - val_tn: 44523.0000 - val_fn: 4.0000 - val_accuracy: 0.9785 - val_precision: 0.0624 - val_recall: 0.9420 - val_auc: 0.9947 - val_prc: 0.5927\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0688 - tp: 2.0000 - fp: 85.0000 - tn: 1961.0000 - fn: 0.0000e+00 - accuracy: 0.9585 - precision: 0.0230 - recall: 1.0000 - auc: 0.9980 - prc: 0.2000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.2954 - tp: 47.0000 - fp: 1053.0000 - tn: 25520.0000 - fn: 4.0000 - accuracy: 0.9603 - precision: 0.0427 - recall: 0.9216 - auc: 0.9452 - prc: 0.2695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.4214 - tp: 84.0000 - fp: 2031.0000 - tn: 49069.0000 - fn: 16.0000 - accuracy: 0.9600 - precision: 0.0397 - recall: 0.8400 - auc: 0.9234 - prc: 0.2119"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "37/90 [===========>..................] - ETA: 0s - loss: 0.3137 - tp: 124.0000 - fp: 3006.0000 - tn: 72630.0000 - fn: 16.0000 - accuracy: 0.9601 - precision: 0.0396 - recall: 0.8857 - auc: 0.9439 - prc: 0.2179"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.3933 - tp: 160.0000 - fp: 4100.0000 - tn: 98112.0000 - fn: 28.0000 - accuracy: 0.9597 - precision: 0.0376 - recall: 0.8511 - auc: 0.9269 - prc: 0.1914"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.3899 - tp: 189.0000 - fp: 5177.0000 - tn: 123622.0000 - fn: 36.0000 - accuracy: 0.9596 - precision: 0.0352 - recall: 0.8400 - auc: 0.9260 - prc: 0.1812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.4104 - tp: 223.0000 - fp: 6195.0000 - tn: 147137.0000 - fn: 45.0000 - accuracy: 0.9594 - precision: 0.0347 - recall: 0.8321 - auc: 0.9205 - prc: 0.1856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.3826 - tp: 255.0000 - fp: 7159.0000 - tn: 170715.0000 - fn: 47.0000 - accuracy: 0.9596 - precision: 0.0344 - recall: 0.8444 - auc: 0.9244 - prc: 0.1776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3757 - tp: 269.0000 - fp: 7315.0000 - tn: 174645.0000 - fn: 47.0000 - accuracy: 0.9596 - precision: 0.0355 - recall: 0.8513 - auc: 0.9277 - prc: 0.1830 - val_loss: 0.0779 - val_tp: 65.0000 - val_fp: 949.0000 - val_tn: 44551.0000 - val_fn: 4.0000 - val_accuracy: 0.9791 - val_precision: 0.0641 - val_recall: 0.9420 - val_auc: 0.9948 - val_prc: 0.5936\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0611 - tp: 1.0000 - fp: 81.0000 - tn: 1966.0000 - fn: 0.0000e+00 - accuracy: 0.9604 - precision: 0.0122 - recall: 1.0000 - auc: 0.9983 - prc: 0.1250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/90 [===>..........................] - ETA: 0s - loss: 0.2046 - tp: 41.0000 - fp: 1075.0000 - tn: 25504.0000 - fn: 4.0000 - accuracy: 0.9595 - precision: 0.0367 - recall: 0.9111 - auc: 0.9675 - prc: 0.2284"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "25/90 [=======>......................] - ETA: 0s - loss: 0.2874 - tp: 80.0000 - fp: 2062.0000 - tn: 49048.0000 - fn: 10.0000 - accuracy: 0.9595 - precision: 0.0373 - recall: 0.8889 - auc: 0.9484 - prc: 0.1983"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.2952 - tp: 124.0000 - fp: 3115.0000 - tn: 74568.0000 - fn: 17.0000 - accuracy: 0.9598 - precision: 0.0383 - recall: 0.8794 - auc: 0.9521 - prc: 0.1919"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "50/90 [===============>..............] - ETA: 0s - loss: 0.2724 - tp: 163.0000 - fp: 4033.0000 - tn: 98184.0000 - fn: 20.0000 - accuracy: 0.9604 - precision: 0.0388 - recall: 0.8907 - auc: 0.9554 - prc: 0.2088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "62/90 [===================>..........] - ETA: 0s - loss: 0.3483 - tp: 196.0000 - fp: 4959.0000 - tn: 121787.0000 - fn: 34.0000 - accuracy: 0.9607 - precision: 0.0380 - recall: 0.8522 - auc: 0.9418 - prc: 0.1933"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.3161 - tp: 231.0000 - fp: 6016.0000 - tn: 147316.0000 - fn: 37.0000 - accuracy: 0.9606 - precision: 0.0370 - recall: 0.8619 - auc: 0.9473 - prc: 0.1892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.3187 - tp: 268.0000 - fp: 6996.0000 - tn: 170868.0000 - fn: 44.0000 - accuracy: 0.9605 - precision: 0.0369 - recall: 0.8590 - auc: 0.9478 - prc: 0.1887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3146 - tp: 271.0000 - fp: 7173.0000 - tn: 174787.0000 - fn: 45.0000 - accuracy: 0.9604 - precision: 0.0364 - recall: 0.8576 - auc: 0.9483 - prc: 0.1861 - val_loss: 0.0790 - val_tp: 65.0000 - val_fp: 944.0000 - val_tn: 44556.0000 - val_fn: 4.0000 - val_accuracy: 0.9792 - val_precision: 0.0644 - val_recall: 0.9420 - val_auc: 0.9948 - val_prc: 0.5963\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0769 - tp: 2.0000 - fp: 89.0000 - tn: 1957.0000 - fn: 0.0000e+00 - accuracy: 0.9565 - precision: 0.0220 - recall: 1.0000 - auc: 0.9976 - prc: 0.1667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.3100 - tp: 43.0000 - fp: 1139.0000 - tn: 27483.0000 - fn: 7.0000 - accuracy: 0.9600 - precision: 0.0364 - recall: 0.8600 - auc: 0.9529 - prc: 0.2147"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.2894 - tp: 82.0000 - fp: 2117.0000 - tn: 51037.0000 - fn: 12.0000 - accuracy: 0.9600 - precision: 0.0373 - recall: 0.8723 - auc: 0.9558 - prc: 0.2073"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "38/90 [===========>..................] - ETA: 0s - loss: 0.3405 - tp: 124.0000 - fp: 3074.0000 - tn: 74607.0000 - fn: 19.0000 - accuracy: 0.9603 - precision: 0.0388 - recall: 0.8671 - auc: 0.9422 - prc: 0.1983"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "51/90 [================>.............] - ETA: 0s - loss: 0.3089 - tp: 164.0000 - fp: 4151.0000 - tn: 100111.0000 - fn: 22.0000 - accuracy: 0.9600 - precision: 0.0380 - recall: 0.8817 - auc: 0.9453 - prc: 0.2024"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "63/90 [====================>.........] - ETA: 0s - loss: 0.2841 - tp: 190.0000 - fp: 5057.0000 - tn: 123752.0000 - fn: 25.0000 - accuracy: 0.9606 - precision: 0.0362 - recall: 0.8837 - auc: 0.9489 - prc: 0.1961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "75/90 [========================>.....] - ETA: 0s - loss: 0.2884 - tp: 227.0000 - fp: 6077.0000 - tn: 147266.0000 - fn: 30.0000 - accuracy: 0.9602 - precision: 0.0360 - recall: 0.8833 - auc: 0.9484 - prc: 0.1964"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "87/90 [============================>.] - ETA: 0s - loss: 0.3226 - tp: 268.0000 - fp: 7036.0000 - tn: 170831.0000 - fn: 41.0000 - accuracy: 0.9603 - precision: 0.0367 - recall: 0.8673 - auc: 0.9444 - prc: 0.1947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 11.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 1s 6ms/step - loss: 0.3172 - tp: 275.0000 - fp: 7203.0000 - tn: 174757.0000 - fn: 41.0000 - accuracy: 0.9603 - precision: 0.0368 - recall: 0.8703 - auc: 0.9455 - prc: 0.1949 - val_loss: 0.0773 - val_tp: 65.0000 - val_fp: 908.0000 - val_tn: 44592.0000 - val_fn: 4.0000 - val_accuracy: 0.9800 - val_precision: 0.0668 - val_recall: 0.9420 - val_auc: 0.9950 - val_prc: 0.6021\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21: early stopping\n"
     ]
    }
   ],
   "source": [
    "weighted_model = make_model()\n",
    "weighted_model.load_weights(initial_weights)\n",
    "\n",
    "weighted_history = weighted_model.fit(\n",
    "    train_features,\n",
    "    train_labels,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    epochs=EPOCHS,\n",
    "    callbacks = [early_stopping],\n",
    "    validation_data=(val_features, val_labels),\n",
    "    # The class weights go here\n",
    "    class_weight=class_weight) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R0ynYRO0G3Lx"
   },
   "source": [
    "### 查看训练历史记录"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:32.878814Z",
     "iopub.status.busy": "2023-11-08T01:17:32.878189Z",
     "iopub.status.idle": "2023-11-08T01:17:33.568234Z",
     "shell.execute_reply": "2023-11-08T01:17:33.567408Z"
    },
    "id": "BBe9FMO5ucTC"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_metrics(weighted_history)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "REy6WClTZIwQ"
   },
   "source": [
    "### 评估指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:33.573106Z",
     "iopub.status.busy": "2023-11-08T01:17:33.572411Z",
     "iopub.status.idle": "2023-11-08T01:17:34.092495Z",
     "shell.execute_reply": "2023-11-08T01:17:34.091553Z"
    },
    "id": "nifqscPGw-5w"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 7s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "34/90 [==========>...................] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 1ms/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/28 [>.............................] - ETA: 1s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/28 [==============================] - 0s 2ms/step\n"
     ]
    }
   ],
   "source": [
    "train_predictions_weighted = weighted_model.predict(train_features, batch_size=BATCH_SIZE)\n",
    "test_predictions_weighted = weighted_model.predict(test_features, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:34.096773Z",
     "iopub.status.busy": "2023-11-08T01:17:34.096223Z",
     "iopub.status.idle": "2023-11-08T01:17:34.495335Z",
     "shell.execute_reply": "2023-11-08T01:17:34.494521Z"
    },
    "id": "owKL2vdMBJr6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.054440323263406754\n",
      "tp :  94.0\n",
      "fp :  832.0\n",
      "tn :  56023.0\n",
      "fn :  13.0\n",
      "accuracy :  0.985165536403656\n",
      "precision :  0.1015118807554245\n",
      "recall :  0.8785046935081482\n",
      "auc :  0.9787468910217285\n",
      "prc :  0.6335744857788086\n",
      "\n",
      "Legitimate Transactions Detected (True Negatives):  56023\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  832\n",
      "Fraudulent Transactions Missed (False Negatives):  13\n",
      "Fraudulent Transactions Detected (True Positives):  94\n",
      "Total Fraudulent Transactions:  107\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weighted_results = weighted_model.evaluate(test_features, test_labels,\n",
    "                                           batch_size=BATCH_SIZE, verbose=0)\n",
    "for name, value in zip(weighted_model.metrics_names, weighted_results):\n",
    "  print(name, ': ', value)\n",
    "print()\n",
    "\n",
    "plot_cm(test_labels, test_predictions_weighted)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PTh1rtDn8r4-"
   },
   "source": [
    "在这里，您可以看到，使用类权重时，由于存在更多假正例，准确率和精确率较低，但是相反，由于模型也找到了更多真正例，召回率和 AUC 较高。尽管准确率较低，但是此模型具有较高的召回率（且识别出了更多欺诈交易）。当然，两种类型的错误都有代价（您也不希望因将过多合法交易标记为欺诈来打扰客户）。请在应用时认真权衡这些不同类型的错误。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hXDAwyr0HYdX"
   },
   "source": [
    "### 绘制 ROC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:34.499182Z",
     "iopub.status.busy": "2023-11-08T01:17:34.498677Z",
     "iopub.status.idle": "2023-11-08T01:17:34.850861Z",
     "shell.execute_reply": "2023-11-08T01:17:34.850102Z"
    },
    "id": "3hzScIVZS1Xm"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "\n",
    "plot_roc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
    "plot_roc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
    "\n",
    "\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_0krS8g1OTbD"
   },
   "source": [
    "### 绘制 AUPRC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:34.855000Z",
     "iopub.status.busy": "2023-11-08T01:17:34.854540Z",
     "iopub.status.idle": "2023-11-08T01:17:35.233752Z",
     "shell.execute_reply": "2023-11-08T01:17:35.232967Z"
    },
    "id": "7jHnmVebOWOC"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "\n",
    "plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
    "plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
    "\n",
    "\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5ysRtr6xHnXP"
   },
   "source": [
    "## 过采样"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "18VUHNc-UF5w"
   },
   "source": [
    "### 对占少数的类进行过采样\n",
    "\n",
    "一种相关方法是通过对占少数的类进行过采样来对数据集进行重新采样。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.238387Z",
     "iopub.status.busy": "2023-11-08T01:17:35.237849Z",
     "iopub.status.idle": "2023-11-08T01:17:35.263971Z",
     "shell.execute_reply": "2023-11-08T01:17:35.263108Z"
    },
    "id": "sHirNp6u7OWp"
   },
   "outputs": [],
   "source": [
    "pos_features = train_features[bool_train_labels]\n",
    "neg_features = train_features[~bool_train_labels]\n",
    "\n",
    "pos_labels = train_labels[bool_train_labels]\n",
    "neg_labels = train_labels[~bool_train_labels]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WgBVbX7P7QrL"
   },
   "source": [
    "#### 使用 NumPy\n",
    "\n",
    "您可以通过从正样本中选择正确数量的随机索引来手动平衡数据集："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.268649Z",
     "iopub.status.busy": "2023-11-08T01:17:35.268076Z",
     "iopub.status.idle": "2023-11-08T01:17:35.293737Z",
     "shell.execute_reply": "2023-11-08T01:17:35.292992Z"
    },
    "id": "BUzGjSkwqT88"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(181960, 29)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ids = np.arange(len(pos_features))\n",
    "choices = np.random.choice(ids, len(neg_features))\n",
    "\n",
    "res_pos_features = pos_features[choices]\n",
    "res_pos_labels = pos_labels[choices]\n",
    "\n",
    "res_pos_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.297669Z",
     "iopub.status.busy": "2023-11-08T01:17:35.297097Z",
     "iopub.status.idle": "2023-11-08T01:17:35.406286Z",
     "shell.execute_reply": "2023-11-08T01:17:35.405535Z"
    },
    "id": "7ie_FFet6cep"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(363920, 29)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resampled_features = np.concatenate([res_pos_features, neg_features], axis=0)\n",
    "resampled_labels = np.concatenate([res_pos_labels, neg_labels], axis=0)\n",
    "\n",
    "order = np.arange(len(resampled_labels))\n",
    "np.random.shuffle(order)\n",
    "resampled_features = resampled_features[order]\n",
    "resampled_labels = resampled_labels[order]\n",
    "\n",
    "resampled_features.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IYfJe2Kc-FAz"
   },
   "source": [
    "#### 使用 `tf.data`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "usyixaST8v5P"
   },
   "source": [
    "如果您使用的是 `tf.data`，则生成平衡样本最简单的方法是从 `positive` 和 `negative` 数据集开始，然后将它们合并。有关更多示例，请参阅 [tf.data 指南](../../guide/data.ipynb)。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.410735Z",
     "iopub.status.busy": "2023-11-08T01:17:35.410422Z",
     "iopub.status.idle": "2023-11-08T01:17:35.538260Z",
     "shell.execute_reply": "2023-11-08T01:17:35.537087Z"
    },
    "id": "yF4OZ-rI6xb6"
   },
   "outputs": [],
   "source": [
    "BUFFER_SIZE = 100000\n",
    "\n",
    "def make_ds(features, labels):\n",
    "  ds = tf.data.Dataset.from_tensor_slices((features, labels))#.cache()\n",
    "  ds = ds.shuffle(BUFFER_SIZE).repeat()\n",
    "  return ds\n",
    "\n",
    "pos_ds = make_ds(pos_features, pos_labels)\n",
    "neg_ds = make_ds(neg_features, neg_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RNQUx-OA-oJc"
   },
   "source": [
    "每个数据集都会提供 `(feature, label)` 对："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.543427Z",
     "iopub.status.busy": "2023-11-08T01:17:35.542583Z",
     "iopub.status.idle": "2023-11-08T01:17:35.561614Z",
     "shell.execute_reply": "2023-11-08T01:17:35.560816Z"
    },
    "id": "llXc9rNH7Fbz"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Features:\n",
      " [ 0.9559428   0.80097054 -1.53757364  2.98558412  0.98626604 -0.64296745\n",
      "  0.58623809 -0.1389485  -1.36773827  0.23749502  1.42062045 -0.28331678\n",
      " -0.7594046  -2.88674106 -1.86392462  1.81905823  2.28344955  1.42037765\n",
      " -1.88417858 -0.29778025 -0.2085476  -0.49742697  0.06843843 -0.3974017\n",
      "  0.32761487 -0.00762779 -0.06715681  0.01644712 -0.48884179]\n",
      "\n",
      "Label:  1\n"
     ]
    }
   ],
   "source": [
    "for features, label in pos_ds.take(1):\n",
    "  print(\"Features:\\n\", features.numpy())\n",
    "  print()\n",
    "  print(\"Label: \", label.numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sLEfjZO0-vbN"
   },
   "source": [
    "使用 `experimental.sample_from_datasets` 将二者合并起来："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.565678Z",
     "iopub.status.busy": "2023-11-08T01:17:35.564987Z",
     "iopub.status.idle": "2023-11-08T01:17:35.590575Z",
     "shell.execute_reply": "2023-11-08T01:17:35.589765Z"
    },
    "id": "e7w9UQPT9wzE"
   },
   "outputs": [],
   "source": [
    "resampled_ds = tf.data.Dataset.sample_from_datasets([pos_ds, neg_ds], weights=[0.5, 0.5])\n",
    "resampled_ds = resampled_ds.batch(BATCH_SIZE).prefetch(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.595297Z",
     "iopub.status.busy": "2023-11-08T01:17:35.594592Z",
     "iopub.status.idle": "2023-11-08T01:17:35.897788Z",
     "shell.execute_reply": "2023-11-08T01:17:35.896741Z"
    },
    "id": "EWXARdTdAuQK"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.49072265625\n"
     ]
    }
   ],
   "source": [
    "for features, label in resampled_ds.take(1):\n",
    "  print(label.numpy().mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "irgqf3YxAyN0"
   },
   "source": [
    "要使用此数据集，您需要每个周期的步骤数。\n",
    "\n",
    "在这种情况下，“周期”的定义就不那么明确了。假设它是遍历一次所有负样本所需的批次数量："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.902076Z",
     "iopub.status.busy": "2023-11-08T01:17:35.901474Z",
     "iopub.status.idle": "2023-11-08T01:17:35.906753Z",
     "shell.execute_reply": "2023-11-08T01:17:35.906090Z"
    },
    "id": "xH-7K46AAxpq"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "278.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resampled_steps_per_epoch = np.ceil(2.0*neg/BATCH_SIZE)\n",
    "resampled_steps_per_epoch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XZ1BvEpcBVHP"
   },
   "source": [
    "### 在过采样数据上进行训练\n",
    "\n",
    "现在尝试使用重新采样后的数据集（而非使用类权重）来训练模型，对比一下这两种方法有何区别。\n",
    "\n",
    "注：因为数据平衡是通过复制正样本实现的，所以数据集的总大小变大了，且每个周期运行的训练步骤也增加了。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:17:35.910671Z",
     "iopub.status.busy": "2023-11-08T01:17:35.910031Z",
     "iopub.status.idle": "2023-11-08T01:18:55.962487Z",
     "shell.execute_reply": "2023-11-08T01:18:55.961782Z"
    },
    "id": "soRQ89JYqd6b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 7:59 - loss: 2.3720 - tp: 378.0000 - fp: 964.0000 - tn: 56895.0000 - fn: 773.0000 - accuracy: 0.9706 - precision: 0.2817 - recall: 0.3284 - auc: 0.7089 - prc: 0.2678"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  6/278 [..............................] - ETA: 3s - loss: 2.2077 - tp: 1832.0000 - fp: 1739.0000 - tn: 61275.0000 - fn: 4404.0000 - accuracy: 0.9113 - precision: 0.5130 - recall: 0.2938 - auc: 0.6839 - prc: 0.3834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  9/278 [..............................] - ETA: 4s - loss: 2.1251 - tp: 2842.0000 - fp: 2171.0000 - tn: 63901.0000 - fn: 6480.0000 - accuracy: 0.8853 - precision: 0.5669 - recall: 0.3049 - auc: 0.6801 - prc: 0.4292"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 2.0811 - tp: 3547.0000 - fp: 2483.0000 - tn: 65597.0000 - fn: 7863.0000 - accuracy: 0.8698 - precision: 0.5882 - recall: 0.3109 - auc: 0.6783 - prc: 0.4517"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/278 [>.............................] - ETA: 5s - loss: 2.0378 - tp: 4273.0000 - fp: 2814.0000 - tn: 67312.0000 - fn: 9187.0000 - accuracy: 0.8564 - precision: 0.6029 - recall: 0.3175 - auc: 0.6760 - prc: 0.4711"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/278 [>.............................] - ETA: 5s - loss: 1.9644 - tp: 5444.0000 - fp: 3299.0000 - tn: 69846.0000 - fn: 11141.0000 - accuracy: 0.8391 - precision: 0.6227 - recall: 0.3282 - auc: 0.6759 - prc: 0.4985"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/278 [=>............................] - ETA: 5s - loss: 1.9044 - tp: 6649.0000 - fp: 3794.0000 - tn: 72423.0000 - fn: 13008.0000 - accuracy: 0.8247 - precision: 0.6367 - recall: 0.3383 - auc: 0.6752 - prc: 0.5196"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/278 [=>............................] - ETA: 5s - loss: 1.8524 - tp: 7904.0000 - fp: 4304.0000 - tn: 74938.0000 - fn: 14872.0000 - accuracy: 0.8120 - precision: 0.6474 - recall: 0.3470 - auc: 0.6745 - prc: 0.5378"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 1.7976 - tp: 9224.0000 - fp: 4839.0000 - tn: 77454.0000 - fn: 16645.0000 - accuracy: 0.8014 - precision: 0.6559 - recall: 0.3566 - auc: 0.6750 - prc: 0.5546"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 5s - loss: 1.7495 - tp: 10566.0000 - fp: 5398.0000 - tn: 79940.0000 - fn: 18402.0000 - accuracy: 0.7918 - precision: 0.6619 - recall: 0.3647 - auc: 0.6749 - prc: 0.5685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/278 [==>...........................] - ETA: 5s - loss: 1.6957 - tp: 11944.0000 - fp: 5946.0000 - tn: 82525.0000 - fn: 20035.0000 - accuracy: 0.7843 - precision: 0.6676 - recall: 0.3735 - auc: 0.6760 - prc: 0.5814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 1.6509 - tp: 13334.0000 - fp: 6529.0000 - tn: 85088.0000 - fn: 21643.0000 - accuracy: 0.7775 - precision: 0.6713 - recall: 0.3812 - auc: 0.6763 - prc: 0.5922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 1.6082 - tp: 14843.0000 - fp: 7101.0000 - tn: 87513.0000 - fn: 23281.0000 - accuracy: 0.7711 - precision: 0.6764 - recall: 0.3893 - auc: 0.6780 - prc: 0.6040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/278 [===>..........................] - ETA: 5s - loss: 1.5675 - tp: 16360.0000 - fp: 7676.0000 - tn: 90019.0000 - fn: 24827.0000 - accuracy: 0.7660 - precision: 0.6806 - recall: 0.3972 - auc: 0.6794 - prc: 0.6141"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/278 [===>..........................] - ETA: 4s - loss: 1.5271 - tp: 17866.0000 - fp: 8303.0000 - tn: 92499.0000 - fn: 26358.0000 - accuracy: 0.7610 - precision: 0.6827 - recall: 0.4040 - auc: 0.6808 - prc: 0.6228"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/278 [===>..........................] - ETA: 4s - loss: 1.4914 - tp: 19485.0000 - fp: 8936.0000 - tn: 94919.0000 - fn: 27830.0000 - accuracy: 0.7568 - precision: 0.6856 - recall: 0.4118 - auc: 0.6828 - prc: 0.6319"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/278 [====>.........................] - ETA: 4s - loss: 1.4574 - tp: 21119.0000 - fp: 9559.0000 - tn: 97391.0000 - fn: 29245.0000 - accuracy: 0.7533 - precision: 0.6884 - recall: 0.4193 - auc: 0.6845 - prc: 0.6401"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/278 [====>.........................] - ETA: 4s - loss: 1.4350 - tp: 22215.0000 - fp: 9957.0000 - tn: 99041.0000 - fn: 30197.0000 - accuracy: 0.7512 - precision: 0.6905 - recall: 0.4239 - auc: 0.6859 - prc: 0.6454"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 4s - loss: 1.4149 - tp: 23318.0000 - fp: 10359.0000 - tn: 100703.0000 - fn: 31126.0000 - accuracy: 0.7493 - precision: 0.6924 - recall: 0.4283 - auc: 0.6870 - prc: 0.6501"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/278 [====>.........................] - ETA: 4s - loss: 1.3931 - tp: 24508.0000 - fp: 10773.0000 - tn: 102317.0000 - fn: 32004.0000 - accuracy: 0.7478 - precision: 0.6947 - recall: 0.4337 - auc: 0.6889 - prc: 0.6557"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/278 [=====>........................] - ETA: 4s - loss: 1.3732 - tp: 25682.0000 - fp: 11205.0000 - tn: 103936.0000 - fn: 32875.0000 - accuracy: 0.7462 - precision: 0.6962 - recall: 0.4386 - auc: 0.6904 - prc: 0.6606"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 1.3542 - tp: 26850.0000 - fp: 11627.0000 - tn: 105580.0000 - fn: 33737.0000 - accuracy: 0.7449 - precision: 0.6978 - recall: 0.4432 - auc: 0.6917 - prc: 0.6650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/278 [=====>........................] - ETA: 4s - loss: 1.3343 - tp: 28087.0000 - fp: 12060.0000 - tn: 107151.0000 - fn: 34592.0000 - accuracy: 0.7435 - precision: 0.6996 - recall: 0.4481 - auc: 0.6937 - prc: 0.6702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/278 [=====>........................] - ETA: 4s - loss: 1.3161 - tp: 29343.0000 - fp: 12460.0000 - tn: 108790.0000 - fn: 35393.0000 - accuracy: 0.7427 - precision: 0.7019 - recall: 0.4533 - auc: 0.6956 - prc: 0.6750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 1.2986 - tp: 30601.0000 - fp: 12900.0000 - tn: 110396.0000 - fn: 36185.0000 - accuracy: 0.7418 - precision: 0.7035 - recall: 0.4582 - auc: 0.6973 - prc: 0.6793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/278 [======>.......................] - ETA: 4s - loss: 1.2810 - tp: 31841.0000 - fp: 13314.0000 - tn: 112032.0000 - fn: 36991.0000 - accuracy: 0.7409 - precision: 0.7051 - recall: 0.4626 - auc: 0.6990 - prc: 0.6837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/278 [======>.......................] - ETA: 4s - loss: 1.2562 - tp: 33769.0000 - fp: 13922.0000 - tn: 114482.0000 - fn: 38149.0000 - accuracy: 0.7401 - precision: 0.7081 - recall: 0.4695 - auc: 0.7016 - prc: 0.6901"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/278 [======>.......................] - ETA: 4s - loss: 1.2318 - tp: 35741.0000 - fp: 14537.0000 - tn: 116966.0000 - fn: 39222.0000 - accuracy: 0.7396 - precision: 0.7109 - recall: 0.4768 - auc: 0.7044 - prc: 0.6964"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 76/278 [=======>......................] - ETA: 4s - loss: 1.2090 - tp: 37731.0000 - fp: 15166.0000 - tn: 119444.0000 - fn: 40269.0000 - accuracy: 0.7393 - precision: 0.7133 - recall: 0.4837 - auc: 0.7070 - prc: 0.7022"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 1.1879 - tp: 39727.0000 - fp: 15822.0000 - tn: 121871.0000 - fn: 41334.0000 - accuracy: 0.7387 - precision: 0.7152 - recall: 0.4901 - auc: 0.7093 - prc: 0.7076"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/278 [=======>......................] - ETA: 4s - loss: 1.1662 - tp: 41821.0000 - fp: 16419.0000 - tn: 124322.0000 - fn: 42336.0000 - accuracy: 0.7387 - precision: 0.7181 - recall: 0.4969 - auc: 0.7124 - prc: 0.7135"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 1.1452 - tp: 43924.0000 - fp: 17050.0000 - tn: 126807.0000 - fn: 43261.0000 - accuracy: 0.7390 - precision: 0.7204 - recall: 0.5038 - auc: 0.7153 - prc: 0.7190"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/278 [========>.....................] - ETA: 4s - loss: 1.1260 - tp: 46055.0000 - fp: 17661.0000 - tn: 129267.0000 - fn: 44203.0000 - accuracy: 0.7392 - precision: 0.7228 - recall: 0.5103 - auc: 0.7180 - prc: 0.7242"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/278 [========>.....................] - ETA: 4s - loss: 1.1078 - tp: 48182.0000 - fp: 18262.0000 - tn: 131729.0000 - fn: 45157.0000 - accuracy: 0.7394 - precision: 0.7252 - recall: 0.5162 - auc: 0.7206 - prc: 0.7290"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/278 [=========>....................] - ETA: 4s - loss: 1.0899 - tp: 50368.0000 - fp: 18872.0000 - tn: 134211.0000 - fn: 46023.0000 - accuracy: 0.7399 - precision: 0.7274 - recall: 0.5225 - auc: 0.7233 - prc: 0.7338"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 4s - loss: 1.0727 - tp: 52543.0000 - fp: 19475.0000 - tn: 136714.0000 - fn: 46886.0000 - accuracy: 0.7404 - precision: 0.7296 - recall: 0.5284 - auc: 0.7260 - prc: 0.7385"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 4s - loss: 1.0559 - tp: 54758.0000 - fp: 20084.0000 - tn: 139200.0000 - fn: 47720.0000 - accuracy: 0.7410 - precision: 0.7316 - recall: 0.5343 - auc: 0.7287 - prc: 0.7430"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 1.0404 - tp: 57044.0000 - fp: 20663.0000 - tn: 141668.0000 - fn: 48531.0000 - accuracy: 0.7417 - precision: 0.7341 - recall: 0.5403 - auc: 0.7314 - prc: 0.7475"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 1.0248 - tp: 59337.0000 - fp: 21219.0000 - tn: 144201.0000 - fn: 49293.0000 - accuracy: 0.7427 - precision: 0.7366 - recall: 0.5462 - auc: 0.7342 - prc: 0.7519"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 1.0107 - tp: 61615.0000 - fp: 21768.0000 - tn: 146698.0000 - fn: 50113.0000 - accuracy: 0.7435 - precision: 0.7389 - recall: 0.5515 - auc: 0.7367 - prc: 0.7559"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.9970 - tp: 63934.0000 - fp: 22304.0000 - tn: 149177.0000 - fn: 50923.0000 - accuracy: 0.7443 - precision: 0.7414 - recall: 0.5566 - auc: 0.7392 - prc: 0.7599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.9838 - tp: 66210.0000 - fp: 22866.0000 - tn: 151688.0000 - fn: 51718.0000 - accuracy: 0.7450 - precision: 0.7433 - recall: 0.5614 - auc: 0.7416 - prc: 0.7636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.9708 - tp: 68544.0000 - fp: 23414.0000 - tn: 154234.0000 - fn: 52434.0000 - accuracy: 0.7460 - precision: 0.7454 - recall: 0.5666 - auc: 0.7441 - prc: 0.7673"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.9586 - tp: 70847.0000 - fp: 23943.0000 - tn: 156767.0000 - fn: 53213.0000 - accuracy: 0.7468 - precision: 0.7474 - recall: 0.5711 - auc: 0.7464 - prc: 0.7707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.9464 - tp: 73173.0000 - fp: 24455.0000 - tn: 159323.0000 - fn: 53963.0000 - accuracy: 0.7478 - precision: 0.7495 - recall: 0.5755 - auc: 0.7488 - prc: 0.7741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.9350 - tp: 75490.0000 - fp: 24980.0000 - tn: 161897.0000 - fn: 54691.0000 - accuracy: 0.7487 - precision: 0.7514 - recall: 0.5799 - auc: 0.7510 - prc: 0.7773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.9238 - tp: 77862.0000 - fp: 25494.0000 - tn: 164424.0000 - fn: 55422.0000 - accuracy: 0.7496 - precision: 0.7533 - recall: 0.5842 - auc: 0.7533 - prc: 0.7805"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.9132 - tp: 80217.0000 - fp: 25972.0000 - tn: 166985.0000 - fn: 56172.0000 - accuracy: 0.7506 - precision: 0.7554 - recall: 0.5881 - auc: 0.7555 - prc: 0.7836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/278 [=============>................] - ETA: 3s - loss: 0.9027 - tp: 82591.0000 - fp: 26466.0000 - tn: 169580.0000 - fn: 56853.0000 - accuracy: 0.7516 - precision: 0.7573 - recall: 0.5923 - auc: 0.7577 - prc: 0.7866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.8927 - tp: 84998.0000 - fp: 26941.0000 - tn: 172129.0000 - fn: 57566.0000 - accuracy: 0.7526 - precision: 0.7593 - recall: 0.5962 - auc: 0.7599 - prc: 0.7895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.8829 - tp: 87333.0000 - fp: 27444.0000 - tn: 174733.0000 - fn: 58268.0000 - accuracy: 0.7535 - precision: 0.7609 - recall: 0.5998 - auc: 0.7619 - prc: 0.7922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 2s - loss: 0.8734 - tp: 89687.0000 - fp: 27891.0000 - tn: 177389.0000 - fn: 58955.0000 - accuracy: 0.7546 - precision: 0.7628 - recall: 0.6034 - auc: 0.7639 - prc: 0.7948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.8640 - tp: 92095.0000 - fp: 28332.0000 - tn: 180052.0000 - fn: 59587.0000 - accuracy: 0.7558 - precision: 0.7647 - recall: 0.6072 - auc: 0.7660 - prc: 0.7975"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.8549 - tp: 94504.0000 - fp: 28783.0000 - tn: 182686.0000 - fn: 60237.0000 - accuracy: 0.7569 - precision: 0.7665 - recall: 0.6107 - auc: 0.7681 - prc: 0.8001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.8463 - tp: 96913.0000 - fp: 29198.0000 - tn: 185275.0000 - fn: 60968.0000 - accuracy: 0.7578 - precision: 0.7685 - recall: 0.6138 - auc: 0.7701 - prc: 0.8027"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.8381 - tp: 99321.0000 - fp: 29667.0000 - tn: 187875.0000 - fn: 61635.0000 - accuracy: 0.7588 - precision: 0.7700 - recall: 0.6171 - auc: 0.7721 - prc: 0.8051"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.8300 - tp: 101745.0000 - fp: 30073.0000 - tn: 190521.0000 - fn: 62303.0000 - accuracy: 0.7598 - precision: 0.7719 - recall: 0.6202 - auc: 0.7740 - prc: 0.8074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.8221 - tp: 104171.0000 - fp: 30461.0000 - tn: 193162.0000 - fn: 62992.0000 - accuracy: 0.7609 - precision: 0.7737 - recall: 0.6232 - auc: 0.7759 - prc: 0.8097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.8144 - tp: 106538.0000 - fp: 30877.0000 - tn: 195874.0000 - fn: 63641.0000 - accuracy: 0.7619 - precision: 0.7753 - recall: 0.6260 - auc: 0.7777 - prc: 0.8118"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.8069 - tp: 108930.0000 - fp: 31277.0000 - tn: 198588.0000 - fn: 64279.0000 - accuracy: 0.7629 - precision: 0.7769 - recall: 0.6289 - auc: 0.7795 - prc: 0.8139"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.7998 - tp: 111339.0000 - fp: 31705.0000 - tn: 201234.0000 - fn: 64940.0000 - accuracy: 0.7638 - precision: 0.7784 - recall: 0.6316 - auc: 0.7812 - prc: 0.8160"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.7928 - tp: 113740.0000 - fp: 32079.0000 - tn: 203959.0000 - fn: 65584.0000 - accuracy: 0.7649 - precision: 0.7800 - recall: 0.6343 - auc: 0.7829 - prc: 0.8179"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.7858 - tp: 116219.0000 - fp: 32435.0000 - tn: 206623.0000 - fn: 66229.0000 - accuracy: 0.7659 - precision: 0.7818 - recall: 0.6370 - auc: 0.7847 - prc: 0.8200"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.7791 - tp: 118684.0000 - fp: 32771.0000 - tn: 209297.0000 - fn: 66898.0000 - accuracy: 0.7669 - precision: 0.7836 - recall: 0.6395 - auc: 0.7864 - prc: 0.8220"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "183/278 [==================>...........] - ETA: 2s - loss: 0.7745 - tp: 120322.0000 - fp: 33029.0000 - tn: 211097.0000 - fn: 67298.0000 - accuracy: 0.7676 - precision: 0.7846 - recall: 0.6413 - auc: 0.7876 - prc: 0.8233"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "186/278 [===================>..........] - ETA: 2s - loss: 0.7680 - tp: 122773.0000 - fp: 33394.0000 - tn: 213785.0000 - fn: 67938.0000 - accuracy: 0.7686 - precision: 0.7862 - recall: 0.6438 - auc: 0.7893 - prc: 0.8252"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "189/278 [===================>..........] - ETA: 2s - loss: 0.7616 - tp: 125170.0000 - fp: 33724.0000 - tn: 216575.0000 - fn: 68565.0000 - accuracy: 0.7696 - precision: 0.7878 - recall: 0.6461 - auc: 0.7909 - prc: 0.8269"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "192/278 [===================>..........] - ETA: 1s - loss: 0.7554 - tp: 127672.0000 - fp: 34043.0000 - tn: 219256.0000 - fn: 69207.0000 - accuracy: 0.7706 - precision: 0.7895 - recall: 0.6485 - auc: 0.7926 - prc: 0.8288"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "195/278 [====================>.........] - ETA: 1s - loss: 0.7494 - tp: 130116.0000 - fp: 34387.0000 - tn: 221976.0000 - fn: 69843.0000 - accuracy: 0.7716 - precision: 0.7910 - recall: 0.6507 - auc: 0.7942 - prc: 0.8305"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "198/278 [====================>.........] - ETA: 1s - loss: 0.7435 - tp: 132632.0000 - fp: 34689.0000 - tn: 224700.0000 - fn: 70445.0000 - accuracy: 0.7727 - precision: 0.7927 - recall: 0.6531 - auc: 0.7958 - prc: 0.8323"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "201/278 [====================>.........] - ETA: 1s - loss: 0.7377 - tp: 135074.0000 - fp: 35017.0000 - tn: 227456.0000 - fn: 71063.0000 - accuracy: 0.7736 - precision: 0.7941 - recall: 0.6553 - auc: 0.7974 - prc: 0.8340"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "204/278 [=====================>........] - ETA: 1s - loss: 0.7320 - tp: 137490.0000 - fp: 35329.0000 - tn: 230272.0000 - fn: 71663.0000 - accuracy: 0.7746 - precision: 0.7956 - recall: 0.6574 - auc: 0.7989 - prc: 0.8355"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "207/278 [=====================>........] - ETA: 1s - loss: 0.7266 - tp: 139924.0000 - fp: 35649.0000 - tn: 233078.0000 - fn: 72247.0000 - accuracy: 0.7756 - precision: 0.7970 - recall: 0.6595 - auc: 0.8003 - prc: 0.8370"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "210/278 [=====================>........] - ETA: 1s - loss: 0.7213 - tp: 142414.0000 - fp: 35958.0000 - tn: 235787.0000 - fn: 72883.0000 - accuracy: 0.7765 - precision: 0.7984 - recall: 0.6615 - auc: 0.8018 - prc: 0.8385"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.7159 - tp: 144896.0000 - fp: 36242.0000 - tn: 238584.0000 - fn: 73464.0000 - accuracy: 0.7776 - precision: 0.7999 - recall: 0.6636 - auc: 0.8033 - prc: 0.8401"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "216/278 [======================>.......] - ETA: 1s - loss: 0.7108 - tp: 147408.0000 - fp: 36530.0000 - tn: 241332.0000 - fn: 74060.0000 - accuracy: 0.7785 - precision: 0.8014 - recall: 0.6656 - auc: 0.8048 - prc: 0.8416"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.7058 - tp: 149884.0000 - fp: 36861.0000 - tn: 244032.0000 - fn: 74697.0000 - accuracy: 0.7793 - precision: 0.8026 - recall: 0.6674 - auc: 0.8062 - prc: 0.8430"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.7009 - tp: 152387.0000 - fp: 37146.0000 - tn: 246804.0000 - fn: 75281.0000 - accuracy: 0.7803 - precision: 0.8040 - recall: 0.6693 - auc: 0.8075 - prc: 0.8445"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.6959 - tp: 154925.0000 - fp: 37410.0000 - tn: 249576.0000 - fn: 75851.0000 - accuracy: 0.7812 - precision: 0.8055 - recall: 0.6713 - auc: 0.8090 - prc: 0.8460"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.6912 - tp: 157398.0000 - fp: 37695.0000 - tn: 252349.0000 - fn: 76464.0000 - accuracy: 0.7821 - precision: 0.8068 - recall: 0.6730 - auc: 0.8103 - prc: 0.8473"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "231/278 [=======================>......] - ETA: 1s - loss: 0.6867 - tp: 159779.0000 - fp: 37963.0000 - tn: 255197.0000 - fn: 77111.0000 - accuracy: 0.7829 - precision: 0.8080 - recall: 0.6745 - auc: 0.8116 - prc: 0.8485"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.6821 - tp: 162211.0000 - fp: 38222.0000 - tn: 257945.0000 - fn: 77816.0000 - accuracy: 0.7836 - precision: 0.8093 - recall: 0.6758 - auc: 0.8130 - prc: 0.8499"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.6778 - tp: 164520.0000 - fp: 38473.0000 - tn: 260777.0000 - fn: 78568.0000 - accuracy: 0.7842 - precision: 0.8105 - recall: 0.6768 - auc: 0.8142 - prc: 0.8511"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.6734 - tp: 166903.0000 - fp: 38714.0000 - tn: 263602.0000 - fn: 79263.0000 - accuracy: 0.7849 - precision: 0.8117 - recall: 0.6780 - auc: 0.8155 - prc: 0.8523"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.6691 - tp: 169309.0000 - fp: 38961.0000 - tn: 266379.0000 - fn: 79977.0000 - accuracy: 0.7856 - precision: 0.8129 - recall: 0.6792 - auc: 0.8168 - prc: 0.8536"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.6648 - tp: 171671.0000 - fp: 39182.0000 - tn: 269242.0000 - fn: 80675.0000 - accuracy: 0.7863 - precision: 0.8142 - recall: 0.6803 - auc: 0.8181 - prc: 0.8548"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.6608 - tp: 174060.0000 - fp: 39427.0000 - tn: 272019.0000 - fn: 81408.0000 - accuracy: 0.7869 - precision: 0.8153 - recall: 0.6813 - auc: 0.8193 - prc: 0.8560"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.6567 - tp: 176441.0000 - fp: 39635.0000 - tn: 274875.0000 - fn: 82107.0000 - accuracy: 0.7876 - precision: 0.8166 - recall: 0.6824 - auc: 0.8206 - prc: 0.8572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.6527 - tp: 178824.0000 - fp: 39867.0000 - tn: 277715.0000 - fn: 82796.0000 - accuracy: 0.7882 - precision: 0.8177 - recall: 0.6835 - auc: 0.8218 - prc: 0.8583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.6487 - tp: 181164.0000 - fp: 40103.0000 - tn: 280605.0000 - fn: 83474.0000 - accuracy: 0.7889 - precision: 0.8188 - recall: 0.6846 - auc: 0.8230 - prc: 0.8594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.6449 - tp: 183493.0000 - fp: 40347.0000 - tn: 283505.0000 - fn: 84145.0000 - accuracy: 0.7895 - precision: 0.8198 - recall: 0.6856 - auc: 0.8241 - prc: 0.8604"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.6411 - tp: 185899.0000 - fp: 40561.0000 - tn: 286318.0000 - fn: 84856.0000 - accuracy: 0.7901 - precision: 0.8209 - recall: 0.6866 - auc: 0.8253 - prc: 0.8615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.6374 - tp: 188288.0000 - fp: 40797.0000 - tn: 289137.0000 - fn: 85556.0000 - accuracy: 0.7907 - precision: 0.8219 - recall: 0.6876 - auc: 0.8264 - prc: 0.8625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.6338 - tp: 190641.0000 - fp: 41038.0000 - tn: 291972.0000 - fn: 86271.0000 - accuracy: 0.7913 - precision: 0.8229 - recall: 0.6885 - auc: 0.8275 - prc: 0.8635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.6302 - tp: 193047.0000 - fp: 41222.0000 - tn: 294815.0000 - fn: 86982.0000 - accuracy: 0.7919 - precision: 0.8240 - recall: 0.6894 - auc: 0.8286 - prc: 0.8646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.6267 - tp: 195387.0000 - fp: 41424.0000 - tn: 297729.0000 - fn: 87670.0000 - accuracy: 0.7925 - precision: 0.8251 - recall: 0.6903 - auc: 0.8297 - prc: 0.8656"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 9s 26ms/step - loss: 0.6244 - tp: 196970.0000 - fp: 41577.0000 - tn: 299585.0000 - fn: 88174.0000 - accuracy: 0.7928 - precision: 0.8257 - recall: 0.6908 - auc: 0.8304 - prc: 0.8662 - val_loss: 0.1924 - val_tp: 63.0000 - val_fp: 819.0000 - val_tn: 44681.0000 - val_fn: 6.0000 - val_accuracy: 0.9819 - val_precision: 0.0714 - val_recall: 0.9130 - val_auc: 0.9944 - val_prc: 0.7565\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.3036 - tp: 782.0000 - fp: 68.0000 - tn: 959.0000 - fn: 239.0000 - accuracy: 0.8501 - precision: 0.9200 - recall: 0.7659 - auc: 0.9335 - prc: 0.9486"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.3000 - tp: 3970.0000 - fp: 330.0000 - tn: 4801.0000 - fn: 1139.0000 - accuracy: 0.8565 - precision: 0.9233 - recall: 0.7771 - auc: 0.9358 - prc: 0.9511"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.3003 - tp: 6302.0000 - fp: 549.0000 - tn: 7699.0000 - fn: 1834.0000 - accuracy: 0.8546 - precision: 0.9199 - recall: 0.7746 - auc: 0.9356 - prc: 0.9500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.3011 - tp: 8681.0000 - fp: 742.0000 - tn: 10561.0000 - fn: 2544.0000 - accuracy: 0.8541 - precision: 0.9213 - recall: 0.7734 - auc: 0.9351 - prc: 0.9500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.2986 - tp: 11121.0000 - fp: 940.0000 - tn: 13393.0000 - fn: 3218.0000 - accuracy: 0.8550 - precision: 0.9221 - recall: 0.7756 - auc: 0.9364 - prc: 0.9511"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.2979 - tp: 13527.0000 - fp: 1129.0000 - tn: 16249.0000 - fn: 3911.0000 - accuracy: 0.8552 - precision: 0.9230 - recall: 0.7757 - auc: 0.9366 - prc: 0.9515"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.2965 - tp: 15951.0000 - fp: 1326.0000 - tn: 19102.0000 - fn: 4581.0000 - accuracy: 0.8558 - precision: 0.9233 - recall: 0.7769 - auc: 0.9374 - prc: 0.9520"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.2950 - tp: 18367.0000 - fp: 1497.0000 - tn: 21962.0000 - fn: 5278.0000 - accuracy: 0.8562 - precision: 0.9246 - recall: 0.7768 - auc: 0.9385 - prc: 0.9526"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.2948 - tp: 20711.0000 - fp: 1707.0000 - tn: 24902.0000 - fn: 5928.0000 - accuracy: 0.8566 - precision: 0.9239 - recall: 0.7775 - auc: 0.9388 - prc: 0.9526"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.2944 - tp: 23081.0000 - fp: 1896.0000 - tn: 27789.0000 - fn: 6626.0000 - accuracy: 0.8565 - precision: 0.9241 - recall: 0.7770 - auc: 0.9389 - prc: 0.9526"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.2932 - tp: 25414.0000 - fp: 2093.0000 - tn: 30743.0000 - fn: 7286.0000 - accuracy: 0.8569 - precision: 0.9239 - recall: 0.7772 - auc: 0.9394 - prc: 0.9528"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.2927 - tp: 26984.0000 - fp: 2224.0000 - tn: 32710.0000 - fn: 7714.0000 - accuracy: 0.8573 - precision: 0.9239 - recall: 0.7777 - auc: 0.9396 - prc: 0.9528"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.2917 - tp: 29318.0000 - fp: 2403.0000 - tn: 35682.0000 - fn: 8373.0000 - accuracy: 0.8578 - precision: 0.9242 - recall: 0.7779 - auc: 0.9399 - prc: 0.9530"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/278 [===>..........................] - ETA: 5s - loss: 0.2909 - tp: 30933.0000 - fp: 2516.0000 - tn: 37604.0000 - fn: 8819.0000 - accuracy: 0.8581 - precision: 0.9248 - recall: 0.7781 - auc: 0.9403 - prc: 0.9532"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/278 [===>..........................] - ETA: 5s - loss: 0.2906 - tp: 33268.0000 - fp: 2724.0000 - tn: 40532.0000 - fn: 9492.0000 - accuracy: 0.8580 - precision: 0.9243 - recall: 0.7780 - auc: 0.9405 - prc: 0.9532"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/278 [===>..........................] - ETA: 5s - loss: 0.2898 - tp: 35716.0000 - fp: 2907.0000 - tn: 43374.0000 - fn: 10163.0000 - accuracy: 0.8582 - precision: 0.9247 - recall: 0.7785 - auc: 0.9410 - prc: 0.9535"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/278 [====>.........................] - ETA: 5s - loss: 0.2888 - tp: 38092.0000 - fp: 3081.0000 - tn: 46303.0000 - fn: 10828.0000 - accuracy: 0.8585 - precision: 0.9252 - recall: 0.7787 - auc: 0.9415 - prc: 0.9538"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/278 [====>.........................] - ETA: 5s - loss: 0.2876 - tp: 40463.0000 - fp: 3248.0000 - tn: 49280.0000 - fn: 11457.0000 - accuracy: 0.8592 - precision: 0.9257 - recall: 0.7793 - auc: 0.9419 - prc: 0.9540"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/278 [====>.........................] - ETA: 5s - loss: 0.2867 - tp: 42883.0000 - fp: 3424.0000 - tn: 52180.0000 - fn: 12105.0000 - accuracy: 0.8596 - precision: 0.9261 - recall: 0.7799 - auc: 0.9423 - prc: 0.9543"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/278 [=====>........................] - ETA: 5s - loss: 0.2861 - tp: 45227.0000 - fp: 3607.0000 - tn: 55113.0000 - fn: 12789.0000 - accuracy: 0.8595 - precision: 0.9261 - recall: 0.7796 - auc: 0.9426 - prc: 0.9544"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/278 [=====>........................] - ETA: 4s - loss: 0.2856 - tp: 47626.0000 - fp: 3796.0000 - tn: 57990.0000 - fn: 13468.0000 - accuracy: 0.8595 - precision: 0.9262 - recall: 0.7796 - auc: 0.9429 - prc: 0.9546"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/278 [=====>........................] - ETA: 4s - loss: 0.2848 - tp: 49999.0000 - fp: 3969.0000 - tn: 60921.0000 - fn: 14135.0000 - accuracy: 0.8597 - precision: 0.9265 - recall: 0.7796 - auc: 0.9432 - prc: 0.9549"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 66/278 [======>.......................] - ETA: 4s - loss: 0.2841 - tp: 52442.0000 - fp: 4124.0000 - tn: 63756.0000 - fn: 14846.0000 - accuracy: 0.8597 - precision: 0.9271 - recall: 0.7794 - auc: 0.9436 - prc: 0.9552"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/278 [======>.......................] - ETA: 4s - loss: 0.2833 - tp: 54856.0000 - fp: 4280.0000 - tn: 66681.0000 - fn: 15495.0000 - accuracy: 0.8601 - precision: 0.9276 - recall: 0.7797 - auc: 0.9439 - prc: 0.9555"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/278 [======>.......................] - ETA: 4s - loss: 0.2826 - tp: 57265.0000 - fp: 4459.0000 - tn: 69573.0000 - fn: 16159.0000 - accuracy: 0.8602 - precision: 0.9278 - recall: 0.7799 - auc: 0.9443 - prc: 0.9557"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/278 [=======>......................] - ETA: 4s - loss: 0.2819 - tp: 59631.0000 - fp: 4619.0000 - tn: 72541.0000 - fn: 16809.0000 - accuracy: 0.8605 - precision: 0.9281 - recall: 0.7801 - auc: 0.9446 - prc: 0.9559"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 78/278 [=======>......................] - ETA: 4s - loss: 0.2812 - tp: 62052.0000 - fp: 4804.0000 - tn: 75414.0000 - fn: 17474.0000 - accuracy: 0.8605 - precision: 0.9281 - recall: 0.7803 - auc: 0.9449 - prc: 0.9561"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.2807 - tp: 63653.0000 - fp: 4912.0000 - tn: 77356.0000 - fn: 17919.0000 - accuracy: 0.8607 - precision: 0.9284 - recall: 0.7803 - auc: 0.9451 - prc: 0.9562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.2799 - tp: 66105.0000 - fp: 5073.0000 - tn: 80247.0000 - fn: 18559.0000 - accuracy: 0.8610 - precision: 0.9287 - recall: 0.7808 - auc: 0.9455 - prc: 0.9565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 4s - loss: 0.2792 - tp: 68510.0000 - fp: 5248.0000 - tn: 83154.0000 - fn: 19216.0000 - accuracy: 0.8611 - precision: 0.9288 - recall: 0.7810 - auc: 0.9458 - prc: 0.9567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 4s - loss: 0.2788 - tp: 70854.0000 - fp: 5415.0000 - tn: 86066.0000 - fn: 19937.0000 - accuracy: 0.8609 - precision: 0.9290 - recall: 0.7804 - auc: 0.9460 - prc: 0.9568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 4s - loss: 0.2781 - tp: 73285.0000 - fp: 5586.0000 - tn: 88963.0000 - fn: 20582.0000 - accuracy: 0.8611 - precision: 0.9292 - recall: 0.7807 - auc: 0.9463 - prc: 0.9570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 4s - loss: 0.2772 - tp: 75686.0000 - fp: 5748.0000 - tn: 91897.0000 - fn: 21229.0000 - accuracy: 0.8613 - precision: 0.9294 - recall: 0.7810 - auc: 0.9467 - prc: 0.9573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 4s - loss: 0.2765 - tp: 78116.0000 - fp: 5895.0000 - tn: 94803.0000 - fn: 21890.0000 - accuracy: 0.8616 - precision: 0.9298 - recall: 0.7811 - auc: 0.9471 - prc: 0.9575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 4s - loss: 0.2761 - tp: 80553.0000 - fp: 6056.0000 - tn: 97673.0000 - fn: 22566.0000 - accuracy: 0.8616 - precision: 0.9301 - recall: 0.7812 - auc: 0.9473 - prc: 0.9577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.2754 - tp: 82912.0000 - fp: 6214.0000 - tn: 100659.0000 - fn: 23207.0000 - accuracy: 0.8619 - precision: 0.9303 - recall: 0.7813 - auc: 0.9476 - prc: 0.9578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.2748 - tp: 85308.0000 - fp: 6369.0000 - tn: 103587.0000 - fn: 23872.0000 - accuracy: 0.8620 - precision: 0.9305 - recall: 0.7814 - auc: 0.9479 - prc: 0.9580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.2742 - tp: 87724.0000 - fp: 6508.0000 - tn: 106533.0000 - fn: 24515.0000 - accuracy: 0.8623 - precision: 0.9309 - recall: 0.7816 - auc: 0.9482 - prc: 0.9582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.2738 - tp: 89370.0000 - fp: 6612.0000 - tn: 108457.0000 - fn: 24937.0000 - accuracy: 0.8625 - precision: 0.9311 - recall: 0.7818 - auc: 0.9484 - prc: 0.9584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "114/278 [===========>..................] - ETA: 3s - loss: 0.2733 - tp: 90961.0000 - fp: 6706.0000 - tn: 110431.0000 - fn: 25374.0000 - accuracy: 0.8626 - precision: 0.9313 - recall: 0.7819 - auc: 0.9486 - prc: 0.9585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "117/278 [===========>..................] - ETA: 3s - loss: 0.2725 - tp: 93408.0000 - fp: 6848.0000 - tn: 113327.0000 - fn: 26033.0000 - accuracy: 0.8628 - precision: 0.9317 - recall: 0.7820 - auc: 0.9490 - prc: 0.9588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "120/278 [===========>..................] - ETA: 3s - loss: 0.2720 - tp: 95847.0000 - fp: 7005.0000 - tn: 116200.0000 - fn: 26708.0000 - accuracy: 0.8628 - precision: 0.9319 - recall: 0.7821 - auc: 0.9492 - prc: 0.9590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "123/278 [============>.................] - ETA: 3s - loss: 0.2717 - tp: 98218.0000 - fp: 7184.0000 - tn: 119093.0000 - fn: 27409.0000 - accuracy: 0.8627 - precision: 0.9318 - recall: 0.7818 - auc: 0.9494 - prc: 0.9591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "126/278 [============>.................] - ETA: 3s - loss: 0.2711 - tp: 100591.0000 - fp: 7344.0000 - tn: 122055.0000 - fn: 28058.0000 - accuracy: 0.8628 - precision: 0.9320 - recall: 0.7819 - auc: 0.9496 - prc: 0.9592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "129/278 [============>.................] - ETA: 3s - loss: 0.2705 - tp: 103046.0000 - fp: 7481.0000 - tn: 124961.0000 - fn: 28704.0000 - accuracy: 0.8630 - precision: 0.9323 - recall: 0.7821 - auc: 0.9499 - prc: 0.9595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "132/278 [=============>................] - ETA: 3s - loss: 0.2700 - tp: 105422.0000 - fp: 7615.0000 - tn: 127913.0000 - fn: 29386.0000 - accuracy: 0.8631 - precision: 0.9326 - recall: 0.7820 - auc: 0.9501 - prc: 0.9596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/278 [=============>................] - ETA: 3s - loss: 0.2696 - tp: 107830.0000 - fp: 7780.0000 - tn: 130785.0000 - fn: 30085.0000 - accuracy: 0.8630 - precision: 0.9327 - recall: 0.7819 - auc: 0.9503 - prc: 0.9597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "138/278 [=============>................] - ETA: 3s - loss: 0.2692 - tp: 110197.0000 - fp: 7939.0000 - tn: 133732.0000 - fn: 30756.0000 - accuracy: 0.8631 - precision: 0.9328 - recall: 0.7818 - auc: 0.9505 - prc: 0.9598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "141/278 [==============>...............] - ETA: 3s - loss: 0.2687 - tp: 112567.0000 - fp: 8065.0000 - tn: 136713.0000 - fn: 31423.0000 - accuracy: 0.8633 - precision: 0.9331 - recall: 0.7818 - auc: 0.9507 - prc: 0.9600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "144/278 [==============>...............] - ETA: 3s - loss: 0.2681 - tp: 115005.0000 - fp: 8215.0000 - tn: 139639.0000 - fn: 32053.0000 - accuracy: 0.8635 - precision: 0.9333 - recall: 0.7820 - auc: 0.9510 - prc: 0.9601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "147/278 [==============>...............] - ETA: 3s - loss: 0.2676 - tp: 117441.0000 - fp: 8354.0000 - tn: 142558.0000 - fn: 32703.0000 - accuracy: 0.8636 - precision: 0.9336 - recall: 0.7822 - auc: 0.9512 - prc: 0.9603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.2674 - tp: 119041.0000 - fp: 8470.0000 - tn: 144512.0000 - fn: 33129.0000 - accuracy: 0.8637 - precision: 0.9336 - recall: 0.7823 - auc: 0.9513 - prc: 0.9604"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.2668 - tp: 121487.0000 - fp: 8601.0000 - tn: 147444.0000 - fn: 33764.0000 - accuracy: 0.8639 - precision: 0.9339 - recall: 0.7825 - auc: 0.9516 - prc: 0.9606"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.2661 - tp: 123926.0000 - fp: 8741.0000 - tn: 150398.0000 - fn: 34375.0000 - accuracy: 0.8642 - precision: 0.9341 - recall: 0.7829 - auc: 0.9519 - prc: 0.9608"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.2656 - tp: 126419.0000 - fp: 8886.0000 - tn: 153264.0000 - fn: 35015.0000 - accuracy: 0.8643 - precision: 0.9343 - recall: 0.7831 - auc: 0.9521 - prc: 0.9609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.2652 - tp: 128841.0000 - fp: 9053.0000 - tn: 156169.0000 - fn: 35665.0000 - accuracy: 0.8644 - precision: 0.9343 - recall: 0.7832 - auc: 0.9523 - prc: 0.9611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.2646 - tp: 131285.0000 - fp: 9214.0000 - tn: 159099.0000 - fn: 36274.0000 - accuracy: 0.8646 - precision: 0.9344 - recall: 0.7835 - auc: 0.9525 - prc: 0.9612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.2640 - tp: 133676.0000 - fp: 9364.0000 - tn: 162066.0000 - fn: 36910.0000 - accuracy: 0.8647 - precision: 0.9345 - recall: 0.7836 - auc: 0.9528 - prc: 0.9614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.2635 - tp: 136119.0000 - fp: 9499.0000 - tn: 164978.0000 - fn: 37564.0000 - accuracy: 0.8648 - precision: 0.9348 - recall: 0.7837 - auc: 0.9530 - prc: 0.9616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.2631 - tp: 138540.0000 - fp: 9645.0000 - tn: 167880.0000 - fn: 38239.0000 - accuracy: 0.8649 - precision: 0.9349 - recall: 0.7837 - auc: 0.9532 - prc: 0.9617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.2625 - tp: 140942.0000 - fp: 9777.0000 - tn: 170842.0000 - fn: 38887.0000 - accuracy: 0.8650 - precision: 0.9351 - recall: 0.7838 - auc: 0.9534 - prc: 0.9619"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.2620 - tp: 143314.0000 - fp: 9932.0000 - tn: 173850.0000 - fn: 39496.0000 - accuracy: 0.8652 - precision: 0.9352 - recall: 0.7840 - auc: 0.9536 - prc: 0.9620"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.2615 - tp: 145754.0000 - fp: 10068.0000 - tn: 176765.0000 - fn: 40149.0000 - accuracy: 0.8653 - precision: 0.9354 - recall: 0.7840 - auc: 0.9539 - prc: 0.9621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.2612 - tp: 148200.0000 - fp: 10246.0000 - tn: 179631.0000 - fn: 40803.0000 - accuracy: 0.8653 - precision: 0.9353 - recall: 0.7841 - auc: 0.9540 - prc: 0.9622"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "188/278 [===================>..........] - ETA: 2s - loss: 0.2608 - tp: 150574.0000 - fp: 10415.0000 - tn: 182605.0000 - fn: 41430.0000 - accuracy: 0.8653 - precision: 0.9353 - recall: 0.7842 - auc: 0.9542 - prc: 0.9623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/278 [===================>..........] - ETA: 2s - loss: 0.2604 - tp: 153048.0000 - fp: 10553.0000 - tn: 185475.0000 - fn: 42092.0000 - accuracy: 0.8654 - precision: 0.9355 - recall: 0.7843 - auc: 0.9544 - prc: 0.9625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.2600 - tp: 155497.0000 - fp: 10703.0000 - tn: 188382.0000 - fn: 42730.0000 - accuracy: 0.8655 - precision: 0.9356 - recall: 0.7844 - auc: 0.9546 - prc: 0.9626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.2596 - tp: 157903.0000 - fp: 10854.0000 - tn: 191309.0000 - fn: 43390.0000 - accuracy: 0.8656 - precision: 0.9357 - recall: 0.7844 - auc: 0.9548 - prc: 0.9627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.2592 - tp: 160377.0000 - fp: 11002.0000 - tn: 194176.0000 - fn: 44045.0000 - accuracy: 0.8656 - precision: 0.9358 - recall: 0.7845 - auc: 0.9550 - prc: 0.9629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.2588 - tp: 162778.0000 - fp: 11134.0000 - tn: 197146.0000 - fn: 44686.0000 - accuracy: 0.8657 - precision: 0.9360 - recall: 0.7846 - auc: 0.9552 - prc: 0.9630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.2584 - tp: 165272.0000 - fp: 11303.0000 - tn: 200010.0000 - fn: 45303.0000 - accuracy: 0.8658 - precision: 0.9360 - recall: 0.7849 - auc: 0.9553 - prc: 0.9631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.2581 - tp: 167731.0000 - fp: 11450.0000 - tn: 202867.0000 - fn: 45984.0000 - accuracy: 0.8658 - precision: 0.9361 - recall: 0.7848 - auc: 0.9555 - prc: 0.9633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.2578 - tp: 169375.0000 - fp: 11546.0000 - tn: 204798.0000 - fn: 46409.0000 - accuracy: 0.8659 - precision: 0.9362 - recall: 0.7849 - auc: 0.9556 - prc: 0.9633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.2574 - tp: 170974.0000 - fp: 11635.0000 - tn: 206768.0000 - fn: 46847.0000 - accuracy: 0.8659 - precision: 0.9363 - recall: 0.7849 - auc: 0.9558 - prc: 0.9635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.2572 - tp: 172599.0000 - fp: 11739.0000 - tn: 208680.0000 - fn: 47302.0000 - accuracy: 0.8659 - precision: 0.9363 - recall: 0.7849 - auc: 0.9559 - prc: 0.9635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "217/278 [======================>.......] - ETA: 1s - loss: 0.2568 - tp: 174267.0000 - fp: 11809.0000 - tn: 210616.0000 - fn: 47724.0000 - accuracy: 0.8660 - precision: 0.9365 - recall: 0.7850 - auc: 0.9560 - prc: 0.9637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.2566 - tp: 175905.0000 - fp: 11893.0000 - tn: 212570.0000 - fn: 48144.0000 - accuracy: 0.8661 - precision: 0.9367 - recall: 0.7851 - auc: 0.9562 - prc: 0.9637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.2563 - tp: 177507.0000 - fp: 11993.0000 - tn: 214539.0000 - fn: 48569.0000 - accuracy: 0.8662 - precision: 0.9367 - recall: 0.7852 - auc: 0.9563 - prc: 0.9638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "223/278 [=======================>......] - ETA: 1s - loss: 0.2559 - tp: 179157.0000 - fp: 12076.0000 - tn: 216495.0000 - fn: 48976.0000 - accuracy: 0.8663 - precision: 0.9369 - recall: 0.7853 - auc: 0.9565 - prc: 0.9639"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.2556 - tp: 180776.0000 - fp: 12169.0000 - tn: 218442.0000 - fn: 49413.0000 - accuracy: 0.8664 - precision: 0.9369 - recall: 0.7853 - auc: 0.9566 - prc: 0.9640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "227/278 [=======================>......] - ETA: 1s - loss: 0.2553 - tp: 182374.0000 - fp: 12260.0000 - tn: 220412.0000 - fn: 49850.0000 - accuracy: 0.8664 - precision: 0.9370 - recall: 0.7853 - auc: 0.9567 - prc: 0.9641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.2550 - tp: 184075.0000 - fp: 12353.0000 - tn: 222301.0000 - fn: 50263.0000 - accuracy: 0.8665 - precision: 0.9371 - recall: 0.7855 - auc: 0.9568 - prc: 0.9642"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.2546 - tp: 186446.0000 - fp: 12467.0000 - tn: 225325.0000 - fn: 50898.0000 - accuracy: 0.8666 - precision: 0.9373 - recall: 0.7856 - auc: 0.9570 - prc: 0.9643"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 1s - loss: 0.2542 - tp: 188896.0000 - fp: 12617.0000 - tn: 228220.0000 - fn: 51547.0000 - accuracy: 0.8667 - precision: 0.9374 - recall: 0.7856 - auc: 0.9572 - prc: 0.9644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.2537 - tp: 191373.0000 - fp: 12754.0000 - tn: 231159.0000 - fn: 52138.0000 - accuracy: 0.8669 - precision: 0.9375 - recall: 0.7859 - auc: 0.9574 - prc: 0.9646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.2533 - tp: 193777.0000 - fp: 12895.0000 - tn: 234131.0000 - fn: 52765.0000 - accuracy: 0.8670 - precision: 0.9376 - recall: 0.7860 - auc: 0.9576 - prc: 0.9647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.2528 - tp: 196309.0000 - fp: 13017.0000 - tn: 236970.0000 - fn: 53416.0000 - accuracy: 0.8671 - precision: 0.9378 - recall: 0.7861 - auc: 0.9578 - prc: 0.9648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.2524 - tp: 198774.0000 - fp: 13143.0000 - tn: 239924.0000 - fn: 54015.0000 - accuracy: 0.8672 - precision: 0.9380 - recall: 0.7863 - auc: 0.9580 - prc: 0.9650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.2520 - tp: 201204.0000 - fp: 13286.0000 - tn: 242882.0000 - fn: 54628.0000 - accuracy: 0.8674 - precision: 0.9381 - recall: 0.7865 - auc: 0.9581 - prc: 0.9651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "253/278 [==========================>...] - ETA: 0s - loss: 0.2516 - tp: 203648.0000 - fp: 13417.0000 - tn: 245806.0000 - fn: 55273.0000 - accuracy: 0.8674 - precision: 0.9382 - recall: 0.7865 - auc: 0.9583 - prc: 0.9652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.2514 - tp: 205255.0000 - fp: 13517.0000 - tn: 247787.0000 - fn: 55681.0000 - accuracy: 0.8675 - precision: 0.9382 - recall: 0.7866 - auc: 0.9584 - prc: 0.9652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.2510 - tp: 207664.0000 - fp: 13635.0000 - tn: 250771.0000 - fn: 56314.0000 - accuracy: 0.8676 - precision: 0.9384 - recall: 0.7867 - auc: 0.9586 - prc: 0.9654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.2507 - tp: 210018.0000 - fp: 13775.0000 - tn: 253782.0000 - fn: 56953.0000 - accuracy: 0.8677 - precision: 0.9384 - recall: 0.7867 - auc: 0.9587 - prc: 0.9654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.2503 - tp: 212460.0000 - fp: 13902.0000 - tn: 256724.0000 - fn: 57586.0000 - accuracy: 0.8678 - precision: 0.9386 - recall: 0.7868 - auc: 0.9589 - prc: 0.9655"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.2499 - tp: 214853.0000 - fp: 14038.0000 - tn: 259713.0000 - fn: 58212.0000 - accuracy: 0.8679 - precision: 0.9387 - recall: 0.7868 - auc: 0.9590 - prc: 0.9656"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.2495 - tp: 217315.0000 - fp: 14173.0000 - tn: 262614.0000 - fn: 58858.0000 - accuracy: 0.8679 - precision: 0.9388 - recall: 0.7869 - auc: 0.9592 - prc: 0.9658"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.2491 - tp: 219700.0000 - fp: 14308.0000 - tn: 265595.0000 - fn: 59501.0000 - accuracy: 0.8680 - precision: 0.9389 - recall: 0.7869 - auc: 0.9593 - prc: 0.9659"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.2488 - tp: 222150.0000 - fp: 14432.0000 - tn: 268524.0000 - fn: 60142.0000 - accuracy: 0.8681 - precision: 0.9390 - recall: 0.7870 - auc: 0.9595 - prc: 0.9660"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 7s 24ms/step - loss: 0.2485 - tp: 223798.0000 - fp: 14518.0000 - tn: 270446.0000 - fn: 60582.0000 - accuracy: 0.8681 - precision: 0.9391 - recall: 0.7870 - auc: 0.9596 - prc: 0.9661 - val_loss: 0.1043 - val_tp: 66.0000 - val_fp: 746.0000 - val_tn: 44754.0000 - val_fn: 3.0000 - val_accuracy: 0.9836 - val_precision: 0.0813 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7801\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.2252 - tp: 800.0000 - fp: 52.0000 - tn: 985.0000 - fn: 211.0000 - accuracy: 0.8716 - precision: 0.9390 - recall: 0.7913 - auc: 0.9700 - prc: 0.9719"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.2143 - tp: 4065.0000 - fp: 233.0000 - tn: 4874.0000 - fn: 1068.0000 - accuracy: 0.8729 - precision: 0.9458 - recall: 0.7919 - auc: 0.9732 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.2153 - tp: 6474.0000 - fp: 355.0000 - tn: 7829.0000 - fn: 1726.0000 - accuracy: 0.8730 - precision: 0.9480 - recall: 0.7895 - auc: 0.9728 - prc: 0.9755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.2147 - tp: 8915.0000 - fp: 489.0000 - tn: 10753.0000 - fn: 2371.0000 - accuracy: 0.8730 - precision: 0.9480 - recall: 0.7899 - auc: 0.9729 - prc: 0.9756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.2136 - tp: 11321.0000 - fp: 613.0000 - tn: 13747.0000 - fn: 2991.0000 - accuracy: 0.8743 - precision: 0.9486 - recall: 0.7910 - auc: 0.9732 - prc: 0.9759"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.2137 - tp: 13701.0000 - fp: 746.0000 - tn: 16734.0000 - fn: 3635.0000 - accuracy: 0.8742 - precision: 0.9484 - recall: 0.7903 - auc: 0.9732 - prc: 0.9757"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.2144 - tp: 16045.0000 - fp: 881.0000 - tn: 19763.0000 - fn: 4271.0000 - accuracy: 0.8742 - precision: 0.9479 - recall: 0.7898 - auc: 0.9729 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.2140 - tp: 18438.0000 - fp: 1026.0000 - tn: 22745.0000 - fn: 4895.0000 - accuracy: 0.8743 - precision: 0.9473 - recall: 0.7902 - auc: 0.9728 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.2141 - tp: 21004.0000 - fp: 1217.0000 - tn: 25686.0000 - fn: 5341.0000 - accuracy: 0.8768 - precision: 0.9452 - recall: 0.7973 - auc: 0.9726 - prc: 0.9750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.2138 - tp: 23711.0000 - fp: 1376.0000 - tn: 28579.0000 - fn: 5726.0000 - accuracy: 0.8804 - precision: 0.9452 - recall: 0.8055 - auc: 0.9727 - prc: 0.9751"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.2133 - tp: 26418.0000 - fp: 1517.0000 - tn: 31493.0000 - fn: 6108.0000 - accuracy: 0.8837 - precision: 0.9457 - recall: 0.8122 - auc: 0.9728 - prc: 0.9754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.2128 - tp: 28206.0000 - fp: 1619.0000 - tn: 33449.0000 - fn: 6358.0000 - accuracy: 0.8854 - precision: 0.9457 - recall: 0.8161 - auc: 0.9730 - prc: 0.9755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.2127 - tp: 30931.0000 - fp: 1776.0000 - tn: 36323.0000 - fn: 6746.0000 - accuracy: 0.8875 - precision: 0.9457 - recall: 0.8210 - auc: 0.9730 - prc: 0.9756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/278 [===>..........................] - ETA: 5s - loss: 0.2121 - tp: 33669.0000 - fp: 1926.0000 - tn: 39205.0000 - fn: 7120.0000 - accuracy: 0.8896 - precision: 0.9459 - recall: 0.8254 - auc: 0.9732 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/278 [===>..........................] - ETA: 5s - loss: 0.2117 - tp: 35392.0000 - fp: 2021.0000 - tn: 41254.0000 - fn: 7349.0000 - accuracy: 0.8911 - precision: 0.9460 - recall: 0.8281 - auc: 0.9733 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/278 [===>..........................] - ETA: 5s - loss: 0.2116 - tp: 38035.0000 - fp: 2177.0000 - tn: 44230.0000 - fn: 7718.0000 - accuracy: 0.8926 - precision: 0.9459 - recall: 0.8313 - auc: 0.9734 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/278 [====>.........................] - ETA: 5s - loss: 0.2110 - tp: 40751.0000 - fp: 2298.0000 - tn: 47158.0000 - fn: 8097.0000 - accuracy: 0.8943 - precision: 0.9466 - recall: 0.8342 - auc: 0.9736 - prc: 0.9760"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 5s - loss: 0.2109 - tp: 42543.0000 - fp: 2386.0000 - tn: 49111.0000 - fn: 8360.0000 - accuracy: 0.8951 - precision: 0.9469 - recall: 0.8358 - auc: 0.9737 - prc: 0.9761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 5s - loss: 0.2106 - tp: 45196.0000 - fp: 2528.0000 - tn: 52101.0000 - fn: 8719.0000 - accuracy: 0.8964 - precision: 0.9470 - recall: 0.8383 - auc: 0.9738 - prc: 0.9761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 5s - loss: 0.2104 - tp: 47957.0000 - fp: 2675.0000 - tn: 54973.0000 - fn: 9083.0000 - accuracy: 0.8975 - precision: 0.9472 - recall: 0.8408 - auc: 0.9739 - prc: 0.9762"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.2102 - tp: 50654.0000 - fp: 2816.0000 - tn: 57919.0000 - fn: 9443.0000 - accuracy: 0.8985 - precision: 0.9473 - recall: 0.8429 - auc: 0.9739 - prc: 0.9763"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.2098 - tp: 53323.0000 - fp: 2960.0000 - tn: 60908.0000 - fn: 9785.0000 - accuracy: 0.8996 - precision: 0.9474 - recall: 0.8449 - auc: 0.9741 - prc: 0.9763"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.2095 - tp: 56113.0000 - fp: 3112.0000 - tn: 63747.0000 - fn: 10148.0000 - accuracy: 0.9004 - precision: 0.9475 - recall: 0.8468 - auc: 0.9741 - prc: 0.9764"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.2091 - tp: 58790.0000 - fp: 3238.0000 - tn: 66733.0000 - fn: 10503.0000 - accuracy: 0.9013 - precision: 0.9478 - recall: 0.8484 - auc: 0.9743 - prc: 0.9765"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.2091 - tp: 61490.0000 - fp: 3389.0000 - tn: 69654.0000 - fn: 10875.0000 - accuracy: 0.9019 - precision: 0.9478 - recall: 0.8497 - auc: 0.9743 - prc: 0.9765"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.2088 - tp: 64245.0000 - fp: 3526.0000 - tn: 72544.0000 - fn: 11237.0000 - accuracy: 0.9026 - precision: 0.9480 - recall: 0.8511 - auc: 0.9744 - prc: 0.9766"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.2087 - tp: 66900.0000 - fp: 3669.0000 - tn: 75524.0000 - fn: 11603.0000 - accuracy: 0.9032 - precision: 0.9480 - recall: 0.8522 - auc: 0.9744 - prc: 0.9766"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.2085 - tp: 69609.0000 - fp: 3805.0000 - tn: 78462.0000 - fn: 11964.0000 - accuracy: 0.9038 - precision: 0.9482 - recall: 0.8533 - auc: 0.9745 - prc: 0.9767"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.2083 - tp: 72298.0000 - fp: 3940.0000 - tn: 81427.0000 - fn: 12319.0000 - accuracy: 0.9043 - precision: 0.9483 - recall: 0.8544 - auc: 0.9746 - prc: 0.9767"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 0.2081 - tp: 74094.0000 - fp: 4028.0000 - tn: 83409.0000 - fn: 12549.0000 - accuracy: 0.9048 - precision: 0.9484 - recall: 0.8552 - auc: 0.9747 - prc: 0.9768"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/278 [========>.....................] - ETA: 4s - loss: 0.2079 - tp: 76835.0000 - fp: 4176.0000 - tn: 86324.0000 - fn: 12889.0000 - accuracy: 0.9053 - precision: 0.9485 - recall: 0.8563 - auc: 0.9747 - prc: 0.9769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/278 [========>.....................] - ETA: 4s - loss: 0.2078 - tp: 79553.0000 - fp: 4335.0000 - tn: 89257.0000 - fn: 13223.0000 - accuracy: 0.9058 - precision: 0.9483 - recall: 0.8575 - auc: 0.9748 - prc: 0.9769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/278 [=========>....................] - ETA: 4s - loss: 0.2074 - tp: 82279.0000 - fp: 4476.0000 - tn: 92198.0000 - fn: 13559.0000 - accuracy: 0.9063 - precision: 0.9484 - recall: 0.8585 - auc: 0.9749 - prc: 0.9769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 4s - loss: 0.2071 - tp: 85081.0000 - fp: 4632.0000 - tn: 95045.0000 - fn: 13898.0000 - accuracy: 0.9067 - precision: 0.9484 - recall: 0.8596 - auc: 0.9749 - prc: 0.9770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 4s - loss: 0.2070 - tp: 87742.0000 - fp: 4781.0000 - tn: 98033.0000 - fn: 14244.0000 - accuracy: 0.9071 - precision: 0.9483 - recall: 0.8603 - auc: 0.9750 - prc: 0.9770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 0.2070 - tp: 90471.0000 - fp: 4948.0000 - tn: 100954.0000 - fn: 14571.0000 - accuracy: 0.9075 - precision: 0.9481 - recall: 0.8613 - auc: 0.9750 - prc: 0.9770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.2068 - tp: 93183.0000 - fp: 5088.0000 - tn: 103895.0000 - fn: 14922.0000 - accuracy: 0.9078 - precision: 0.9482 - recall: 0.8620 - auc: 0.9751 - prc: 0.9771"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.2066 - tp: 95958.0000 - fp: 5232.0000 - tn: 106781.0000 - fn: 15261.0000 - accuracy: 0.9082 - precision: 0.9483 - recall: 0.8628 - auc: 0.9751 - prc: 0.9771"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.2064 - tp: 98735.0000 - fp: 5387.0000 - tn: 109651.0000 - fn: 15603.0000 - accuracy: 0.9085 - precision: 0.9483 - recall: 0.8635 - auc: 0.9752 - prc: 0.9772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.2062 - tp: 101465.0000 - fp: 5533.0000 - tn: 112568.0000 - fn: 15954.0000 - accuracy: 0.9088 - precision: 0.9483 - recall: 0.8641 - auc: 0.9753 - prc: 0.9773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.2059 - tp: 104195.0000 - fp: 5674.0000 - tn: 115511.0000 - fn: 16284.0000 - accuracy: 0.9091 - precision: 0.9484 - recall: 0.8648 - auc: 0.9753 - prc: 0.9773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.2058 - tp: 106888.0000 - fp: 5830.0000 - tn: 118458.0000 - fn: 16632.0000 - accuracy: 0.9094 - precision: 0.9483 - recall: 0.8653 - auc: 0.9754 - prc: 0.9773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.2057 - tp: 109620.0000 - fp: 5989.0000 - tn: 121386.0000 - fn: 16957.0000 - accuracy: 0.9096 - precision: 0.9482 - recall: 0.8660 - auc: 0.9754 - prc: 0.9773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.2055 - tp: 112349.0000 - fp: 6125.0000 - tn: 124328.0000 - fn: 17294.0000 - accuracy: 0.9100 - precision: 0.9483 - recall: 0.8666 - auc: 0.9755 - prc: 0.9774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.2053 - tp: 115046.0000 - fp: 6261.0000 - tn: 127301.0000 - fn: 17632.0000 - accuracy: 0.9103 - precision: 0.9484 - recall: 0.8671 - auc: 0.9755 - prc: 0.9774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.2051 - tp: 117833.0000 - fp: 6400.0000 - tn: 130181.0000 - fn: 17970.0000 - accuracy: 0.9105 - precision: 0.9485 - recall: 0.8677 - auc: 0.9756 - prc: 0.9775"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/278 [=============>................] - ETA: 3s - loss: 0.2049 - tp: 120530.0000 - fp: 6545.0000 - tn: 133173.0000 - fn: 18280.0000 - accuracy: 0.9109 - precision: 0.9485 - recall: 0.8683 - auc: 0.9756 - prc: 0.9775"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.2049 - tp: 123285.0000 - fp: 6694.0000 - tn: 136052.0000 - fn: 18641.0000 - accuracy: 0.9110 - precision: 0.9485 - recall: 0.8687 - auc: 0.9757 - prc: 0.9776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.2047 - tp: 126061.0000 - fp: 6829.0000 - tn: 138960.0000 - fn: 18966.0000 - accuracy: 0.9113 - precision: 0.9486 - recall: 0.8692 - auc: 0.9757 - prc: 0.9776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 3s - loss: 0.2044 - tp: 128764.0000 - fp: 6964.0000 - tn: 141951.0000 - fn: 19281.0000 - accuracy: 0.9116 - precision: 0.9487 - recall: 0.8698 - auc: 0.9758 - prc: 0.9777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.2041 - tp: 131497.0000 - fp: 7104.0000 - tn: 144919.0000 - fn: 19584.0000 - accuracy: 0.9120 - precision: 0.9487 - recall: 0.8704 - auc: 0.9759 - prc: 0.9777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.2038 - tp: 134231.0000 - fp: 7235.0000 - tn: 147874.0000 - fn: 19908.0000 - accuracy: 0.9122 - precision: 0.9489 - recall: 0.8708 - auc: 0.9760 - prc: 0.9778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.2037 - tp: 136980.0000 - fp: 7386.0000 - tn: 150785.0000 - fn: 20241.0000 - accuracy: 0.9124 - precision: 0.9488 - recall: 0.8713 - auc: 0.9760 - prc: 0.9779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.2035 - tp: 139712.0000 - fp: 7530.0000 - tn: 153741.0000 - fn: 20553.0000 - accuracy: 0.9127 - precision: 0.9489 - recall: 0.8718 - auc: 0.9761 - prc: 0.9779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.2032 - tp: 142401.0000 - fp: 7661.0000 - tn: 156770.0000 - fn: 20848.0000 - accuracy: 0.9130 - precision: 0.9489 - recall: 0.8723 - auc: 0.9762 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.2030 - tp: 145124.0000 - fp: 7803.0000 - tn: 159751.0000 - fn: 21146.0000 - accuracy: 0.9133 - precision: 0.9490 - recall: 0.8728 - auc: 0.9762 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.2029 - tp: 147921.0000 - fp: 7937.0000 - tn: 162635.0000 - fn: 21475.0000 - accuracy: 0.9135 - precision: 0.9491 - recall: 0.8732 - auc: 0.9763 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.2026 - tp: 150706.0000 - fp: 8083.0000 - tn: 165534.0000 - fn: 21789.0000 - accuracy: 0.9137 - precision: 0.9491 - recall: 0.8737 - auc: 0.9763 - prc: 0.9781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.2023 - tp: 153440.0000 - fp: 8222.0000 - tn: 168502.0000 - fn: 22092.0000 - accuracy: 0.9139 - precision: 0.9491 - recall: 0.8741 - auc: 0.9764 - prc: 0.9782"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.2020 - tp: 156165.0000 - fp: 8336.0000 - tn: 171488.0000 - fn: 22411.0000 - accuracy: 0.9142 - precision: 0.9493 - recall: 0.8745 - auc: 0.9765 - prc: 0.9783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "177/278 [==================>...........] - ETA: 2s - loss: 0.2017 - tp: 158032.0000 - fp: 8434.0000 - tn: 173443.0000 - fn: 22587.0000 - accuracy: 0.9144 - precision: 0.9493 - recall: 0.8749 - auc: 0.9766 - prc: 0.9783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.2016 - tp: 159854.0000 - fp: 8534.0000 - tn: 175410.0000 - fn: 22794.0000 - accuracy: 0.9145 - precision: 0.9493 - recall: 0.8752 - auc: 0.9766 - prc: 0.9783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.2014 - tp: 161745.0000 - fp: 8643.0000 - tn: 177297.0000 - fn: 23003.0000 - accuracy: 0.9146 - precision: 0.9493 - recall: 0.8755 - auc: 0.9767 - prc: 0.9784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "183/278 [==================>...........] - ETA: 2s - loss: 0.2013 - tp: 163573.0000 - fp: 8735.0000 - tn: 179261.0000 - fn: 23215.0000 - accuracy: 0.9148 - precision: 0.9493 - recall: 0.8757 - auc: 0.9767 - prc: 0.9784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.2012 - tp: 165425.0000 - fp: 8831.0000 - tn: 181210.0000 - fn: 23414.0000 - accuracy: 0.9149 - precision: 0.9493 - recall: 0.8760 - auc: 0.9767 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 2s - loss: 0.2010 - tp: 167276.0000 - fp: 8922.0000 - tn: 183144.0000 - fn: 23634.0000 - accuracy: 0.9150 - precision: 0.9494 - recall: 0.8762 - auc: 0.9768 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/278 [===================>..........] - ETA: 2s - loss: 0.2009 - tp: 170011.0000 - fp: 9075.0000 - tn: 186104.0000 - fn: 23930.0000 - accuracy: 0.9152 - precision: 0.9493 - recall: 0.8766 - auc: 0.9768 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "192/278 [===================>..........] - ETA: 1s - loss: 0.2009 - tp: 171797.0000 - fp: 9173.0000 - tn: 188105.0000 - fn: 24141.0000 - accuracy: 0.9153 - precision: 0.9493 - recall: 0.8768 - auc: 0.9768 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "195/278 [====================>.........] - ETA: 1s - loss: 0.2008 - tp: 174538.0000 - fp: 9331.0000 - tn: 191049.0000 - fn: 24442.0000 - accuracy: 0.9154 - precision: 0.9493 - recall: 0.8772 - auc: 0.9769 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.2006 - tp: 176388.0000 - fp: 9428.0000 - tn: 193005.0000 - fn: 24635.0000 - accuracy: 0.9156 - precision: 0.9493 - recall: 0.8775 - auc: 0.9769 - prc: 0.9786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.2005 - tp: 179188.0000 - fp: 9581.0000 - tn: 195867.0000 - fn: 24964.0000 - accuracy: 0.9157 - precision: 0.9492 - recall: 0.8777 - auc: 0.9770 - prc: 0.9786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.2003 - tp: 181943.0000 - fp: 9743.0000 - tn: 198776.0000 - fn: 25282.0000 - accuracy: 0.9158 - precision: 0.9492 - recall: 0.8780 - auc: 0.9770 - prc: 0.9786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.2001 - tp: 184775.0000 - fp: 9866.0000 - tn: 201664.0000 - fn: 25583.0000 - accuracy: 0.9160 - precision: 0.9493 - recall: 0.8784 - auc: 0.9771 - prc: 0.9787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1999 - tp: 187542.0000 - fp: 10015.0000 - tn: 204587.0000 - fn: 25888.0000 - accuracy: 0.9161 - precision: 0.9493 - recall: 0.8787 - auc: 0.9771 - prc: 0.9787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1998 - tp: 190357.0000 - fp: 10157.0000 - tn: 207451.0000 - fn: 26211.0000 - accuracy: 0.9162 - precision: 0.9493 - recall: 0.8790 - auc: 0.9772 - prc: 0.9788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1996 - tp: 193102.0000 - fp: 10301.0000 - tn: 210416.0000 - fn: 26501.0000 - accuracy: 0.9164 - precision: 0.9494 - recall: 0.8793 - auc: 0.9772 - prc: 0.9788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1995 - tp: 195809.0000 - fp: 10468.0000 - tn: 213392.0000 - fn: 26795.0000 - accuracy: 0.9165 - precision: 0.9493 - recall: 0.8796 - auc: 0.9773 - prc: 0.9788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.1993 - tp: 198588.0000 - fp: 10611.0000 - tn: 216302.0000 - fn: 27107.0000 - accuracy: 0.9167 - precision: 0.9493 - recall: 0.8799 - auc: 0.9773 - prc: 0.9789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "223/278 [=======================>......] - ETA: 1s - loss: 0.1991 - tp: 200412.0000 - fp: 10698.0000 - tn: 218280.0000 - fn: 27314.0000 - accuracy: 0.9168 - precision: 0.9493 - recall: 0.8801 - auc: 0.9774 - prc: 0.9789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "226/278 [=======================>......] - ETA: 1s - loss: 0.1989 - tp: 203187.0000 - fp: 10846.0000 - tn: 221206.0000 - fn: 27609.0000 - accuracy: 0.9169 - precision: 0.9493 - recall: 0.8804 - auc: 0.9774 - prc: 0.9790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.1988 - tp: 206048.0000 - fp: 10993.0000 - tn: 224061.0000 - fn: 27890.0000 - accuracy: 0.9171 - precision: 0.9494 - recall: 0.8808 - auc: 0.9774 - prc: 0.9790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.1986 - tp: 208814.0000 - fp: 11151.0000 - tn: 226989.0000 - fn: 28182.0000 - accuracy: 0.9172 - precision: 0.9493 - recall: 0.8811 - auc: 0.9775 - prc: 0.9790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1983 - tp: 211583.0000 - fp: 11282.0000 - tn: 229965.0000 - fn: 28450.0000 - accuracy: 0.9174 - precision: 0.9494 - recall: 0.8815 - auc: 0.9776 - prc: 0.9791"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1981 - tp: 214330.0000 - fp: 11419.0000 - tn: 232926.0000 - fn: 28749.0000 - accuracy: 0.9176 - precision: 0.9494 - recall: 0.8817 - auc: 0.9776 - prc: 0.9791"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.1980 - tp: 217117.0000 - fp: 11567.0000 - tn: 235848.0000 - fn: 29036.0000 - accuracy: 0.9177 - precision: 0.9494 - recall: 0.8820 - auc: 0.9776 - prc: 0.9792"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1978 - tp: 219862.0000 - fp: 11729.0000 - tn: 238802.0000 - fn: 29319.0000 - accuracy: 0.9179 - precision: 0.9494 - recall: 0.8823 - auc: 0.9777 - prc: 0.9792"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.1977 - tp: 222648.0000 - fp: 11873.0000 - tn: 241738.0000 - fn: 29597.0000 - accuracy: 0.9180 - precision: 0.9494 - recall: 0.8827 - auc: 0.9777 - prc: 0.9792"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.1974 - tp: 225449.0000 - fp: 12010.0000 - tn: 244657.0000 - fn: 29884.0000 - accuracy: 0.9182 - precision: 0.9494 - recall: 0.8830 - auc: 0.9778 - prc: 0.9793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "253/278 [==========================>...] - ETA: 0s - loss: 0.1972 - tp: 228258.0000 - fp: 12170.0000 - tn: 247557.0000 - fn: 30159.0000 - accuracy: 0.9183 - precision: 0.9494 - recall: 0.8833 - auc: 0.9778 - prc: 0.9793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "256/278 [==========================>...] - ETA: 0s - loss: 0.1970 - tp: 231027.0000 - fp: 12283.0000 - tn: 250534.0000 - fn: 30444.0000 - accuracy: 0.9185 - precision: 0.9495 - recall: 0.8836 - auc: 0.9779 - prc: 0.9794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "259/278 [==========================>...] - ETA: 0s - loss: 0.1969 - tp: 233910.0000 - fp: 12446.0000 - tn: 253358.0000 - fn: 30718.0000 - accuracy: 0.9186 - precision: 0.9495 - recall: 0.8839 - auc: 0.9779 - prc: 0.9794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1968 - tp: 235811.0000 - fp: 12545.0000 - tn: 255265.0000 - fn: 30907.0000 - accuracy: 0.9187 - precision: 0.9495 - recall: 0.8841 - auc: 0.9780 - prc: 0.9795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1966 - tp: 238574.0000 - fp: 12708.0000 - tn: 258203.0000 - fn: 31187.0000 - accuracy: 0.9188 - precision: 0.9494 - recall: 0.8844 - auc: 0.9780 - prc: 0.9795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1964 - tp: 241372.0000 - fp: 12864.0000 - tn: 261121.0000 - fn: 31459.0000 - accuracy: 0.9189 - precision: 0.9494 - recall: 0.8847 - auc: 0.9780 - prc: 0.9795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1962 - tp: 244138.0000 - fp: 13002.0000 - tn: 264098.0000 - fn: 31722.0000 - accuracy: 0.9191 - precision: 0.9494 - recall: 0.8850 - auc: 0.9781 - prc: 0.9796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1961 - tp: 246988.0000 - fp: 13155.0000 - tn: 266949.0000 - fn: 32012.0000 - accuracy: 0.9192 - precision: 0.9494 - recall: 0.8853 - auc: 0.9781 - prc: 0.9796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1959 - tp: 249732.0000 - fp: 13302.0000 - tn: 269941.0000 - fn: 32273.0000 - accuracy: 0.9194 - precision: 0.9494 - recall: 0.8856 - auc: 0.9782 - prc: 0.9796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 7s 23ms/step - loss: 0.1958 - tp: 251598.0000 - fp: 13396.0000 - tn: 271898.0000 - fn: 32452.0000 - accuracy: 0.9195 - precision: 0.9494 - recall: 0.8858 - auc: 0.9782 - prc: 0.9796 - val_loss: 0.0813 - val_tp: 66.0000 - val_fp: 799.0000 - val_tn: 44701.0000 - val_fn: 3.0000 - val_accuracy: 0.9824 - val_precision: 0.0763 - val_recall: 0.9565 - val_auc: 0.9957 - val_prc: 0.7847\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1781 - tp: 902.0000 - fp: 50.0000 - tn: 1006.0000 - fn: 90.0000 - accuracy: 0.9316 - precision: 0.9475 - recall: 0.9093 - auc: 0.9823 - prc: 0.9826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1791 - tp: 4676.0000 - fp: 244.0000 - tn: 4860.0000 - fn: 460.0000 - accuracy: 0.9312 - precision: 0.9504 - recall: 0.9104 - auc: 0.9827 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1803 - tp: 7463.0000 - fp: 390.0000 - tn: 7782.0000 - fn: 749.0000 - accuracy: 0.9305 - precision: 0.9503 - recall: 0.9088 - auc: 0.9823 - prc: 0.9832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1808 - tp: 10207.0000 - fp: 555.0000 - tn: 10745.0000 - fn: 1021.0000 - accuracy: 0.9300 - precision: 0.9484 - recall: 0.9091 - auc: 0.9821 - prc: 0.9826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1803 - tp: 13016.0000 - fp: 690.0000 - tn: 13669.0000 - fn: 1297.0000 - accuracy: 0.9307 - precision: 0.9497 - recall: 0.9094 - auc: 0.9822 - prc: 0.9828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1803 - tp: 15860.0000 - fp: 842.0000 - tn: 16567.0000 - fn: 1547.0000 - accuracy: 0.9314 - precision: 0.9496 - recall: 0.9111 - auc: 0.9821 - prc: 0.9829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1788 - tp: 18681.0000 - fp: 984.0000 - tn: 19503.0000 - fn: 1792.0000 - accuracy: 0.9322 - precision: 0.9500 - recall: 0.9125 - auc: 0.9824 - prc: 0.9832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1781 - tp: 21467.0000 - fp: 1134.0000 - tn: 22453.0000 - fn: 2050.0000 - accuracy: 0.9324 - precision: 0.9498 - recall: 0.9128 - auc: 0.9826 - prc: 0.9833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1772 - tp: 23347.0000 - fp: 1207.0000 - tn: 24427.0000 - fn: 2219.0000 - accuracy: 0.9331 - precision: 0.9508 - recall: 0.9132 - auc: 0.9829 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1778 - tp: 26146.0000 - fp: 1363.0000 - tn: 27334.0000 - fn: 2501.0000 - accuracy: 0.9326 - precision: 0.9505 - recall: 0.9127 - auc: 0.9827 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/278 [==>...........................] - ETA: 5s - loss: 0.1785 - tp: 29003.0000 - fp: 1500.0000 - tn: 30189.0000 - fn: 2796.0000 - accuracy: 0.9323 - precision: 0.9508 - recall: 0.9121 - auc: 0.9826 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.1780 - tp: 31782.0000 - fp: 1624.0000 - tn: 33172.0000 - fn: 3054.0000 - accuracy: 0.9328 - precision: 0.9514 - recall: 0.9123 - auc: 0.9828 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.1780 - tp: 34603.0000 - fp: 1785.0000 - tn: 36067.0000 - fn: 3321.0000 - accuracy: 0.9326 - precision: 0.9509 - recall: 0.9124 - auc: 0.9827 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/278 [===>..........................] - ETA: 5s - loss: 0.1776 - tp: 37387.0000 - fp: 1929.0000 - tn: 39006.0000 - fn: 3598.0000 - accuracy: 0.9325 - precision: 0.9509 - recall: 0.9122 - auc: 0.9828 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/278 [===>..........................] - ETA: 5s - loss: 0.1773 - tp: 40224.0000 - fp: 2069.0000 - tn: 41914.0000 - fn: 3857.0000 - accuracy: 0.9327 - precision: 0.9511 - recall: 0.9125 - auc: 0.9829 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/278 [===>..........................] - ETA: 5s - loss: 0.1773 - tp: 43040.0000 - fp: 2223.0000 - tn: 44844.0000 - fn: 4101.0000 - accuracy: 0.9329 - precision: 0.9509 - recall: 0.9130 - auc: 0.9829 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/278 [====>.........................] - ETA: 5s - loss: 0.1771 - tp: 45821.0000 - fp: 2386.0000 - tn: 47797.0000 - fn: 4348.0000 - accuracy: 0.9329 - precision: 0.9505 - recall: 0.9133 - auc: 0.9829 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/278 [====>.........................] - ETA: 4s - loss: 0.1776 - tp: 47698.0000 - fp: 2519.0000 - tn: 49705.0000 - fn: 4526.0000 - accuracy: 0.9326 - precision: 0.9498 - recall: 0.9133 - auc: 0.9828 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/278 [====>.........................] - ETA: 4s - loss: 0.1776 - tp: 50488.0000 - fp: 2688.0000 - tn: 52635.0000 - fn: 4781.0000 - accuracy: 0.9325 - precision: 0.9495 - recall: 0.9135 - auc: 0.9828 - prc: 0.9833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/278 [=====>........................] - ETA: 4s - loss: 0.1777 - tp: 53334.0000 - fp: 2847.0000 - tn: 55519.0000 - fn: 5036.0000 - accuracy: 0.9325 - precision: 0.9493 - recall: 0.9137 - auc: 0.9827 - prc: 0.9833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/278 [=====>........................] - ETA: 4s - loss: 0.1774 - tp: 56176.0000 - fp: 2991.0000 - tn: 58427.0000 - fn: 5286.0000 - accuracy: 0.9326 - precision: 0.9494 - recall: 0.9140 - auc: 0.9828 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/278 [=====>........................] - ETA: 4s - loss: 0.1772 - tp: 59028.0000 - fp: 3147.0000 - tn: 61317.0000 - fn: 5532.0000 - accuracy: 0.9327 - precision: 0.9494 - recall: 0.9143 - auc: 0.9829 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 66/278 [======>.......................] - ETA: 4s - loss: 0.1769 - tp: 61817.0000 - fp: 3305.0000 - tn: 64288.0000 - fn: 5758.0000 - accuracy: 0.9330 - precision: 0.9492 - recall: 0.9148 - auc: 0.9829 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/278 [======>.......................] - ETA: 4s - loss: 0.1769 - tp: 64603.0000 - fp: 3465.0000 - tn: 67233.0000 - fn: 6011.0000 - accuracy: 0.9329 - precision: 0.9491 - recall: 0.9149 - auc: 0.9829 - prc: 0.9834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/278 [======>.......................] - ETA: 4s - loss: 0.1768 - tp: 67369.0000 - fp: 3593.0000 - tn: 70212.0000 - fn: 6282.0000 - accuracy: 0.9330 - precision: 0.9494 - recall: 0.9147 - auc: 0.9830 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/278 [=======>......................] - ETA: 4s - loss: 0.1766 - tp: 70164.0000 - fp: 3745.0000 - tn: 73149.0000 - fn: 6542.0000 - accuracy: 0.9330 - precision: 0.9493 - recall: 0.9147 - auc: 0.9830 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 78/278 [=======>......................] - ETA: 4s - loss: 0.1766 - tp: 72900.0000 - fp: 3898.0000 - tn: 76139.0000 - fn: 6807.0000 - accuracy: 0.9330 - precision: 0.9492 - recall: 0.9146 - auc: 0.9830 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/278 [=======>......................] - ETA: 4s - loss: 0.1765 - tp: 75765.0000 - fp: 4040.0000 - tn: 79020.0000 - fn: 7063.0000 - accuracy: 0.9331 - precision: 0.9494 - recall: 0.9147 - auc: 0.9830 - prc: 0.9835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/278 [========>.....................] - ETA: 4s - loss: 0.1762 - tp: 78563.0000 - fp: 4185.0000 - tn: 81969.0000 - fn: 7315.0000 - accuracy: 0.9332 - precision: 0.9494 - recall: 0.9148 - auc: 0.9831 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 87/278 [========>.....................] - ETA: 4s - loss: 0.1760 - tp: 81355.0000 - fp: 4317.0000 - tn: 84949.0000 - fn: 7555.0000 - accuracy: 0.9334 - precision: 0.9496 - recall: 0.9150 - auc: 0.9831 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 90/278 [========>.....................] - ETA: 4s - loss: 0.1759 - tp: 84198.0000 - fp: 4480.0000 - tn: 87850.0000 - fn: 7792.0000 - accuracy: 0.9334 - precision: 0.9495 - recall: 0.9153 - auc: 0.9831 - prc: 0.9836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 93/278 [=========>....................] - ETA: 4s - loss: 0.1757 - tp: 87058.0000 - fp: 4628.0000 - tn: 90730.0000 - fn: 8048.0000 - accuracy: 0.9334 - precision: 0.9495 - recall: 0.9154 - auc: 0.9832 - prc: 0.9837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/278 [=========>....................] - ETA: 3s - loss: 0.1755 - tp: 89827.0000 - fp: 4764.0000 - tn: 93725.0000 - fn: 8292.0000 - accuracy: 0.9336 - precision: 0.9496 - recall: 0.9155 - auc: 0.9832 - prc: 0.9837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.1755 - tp: 91712.0000 - fp: 4884.0000 - tn: 95661.0000 - fn: 8447.0000 - accuracy: 0.9336 - precision: 0.9494 - recall: 0.9157 - auc: 0.9832 - prc: 0.9837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1753 - tp: 94600.0000 - fp: 5030.0000 - tn: 98517.0000 - fn: 8701.0000 - accuracy: 0.9336 - precision: 0.9495 - recall: 0.9158 - auc: 0.9832 - prc: 0.9838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1753 - tp: 97514.0000 - fp: 5212.0000 - tn: 101321.0000 - fn: 8945.0000 - accuracy: 0.9335 - precision: 0.9493 - recall: 0.9160 - auc: 0.9832 - prc: 0.9838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1751 - tp: 100421.0000 - fp: 5353.0000 - tn: 104194.0000 - fn: 9168.0000 - accuracy: 0.9337 - precision: 0.9494 - recall: 0.9163 - auc: 0.9833 - prc: 0.9838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1750 - tp: 103268.0000 - fp: 5503.0000 - tn: 107104.0000 - fn: 9405.0000 - accuracy: 0.9338 - precision: 0.9494 - recall: 0.9165 - auc: 0.9833 - prc: 0.9838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1749 - tp: 106107.0000 - fp: 5644.0000 - tn: 110021.0000 - fn: 9652.0000 - accuracy: 0.9339 - precision: 0.9495 - recall: 0.9166 - auc: 0.9833 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1748 - tp: 108917.0000 - fp: 5795.0000 - tn: 112962.0000 - fn: 9894.0000 - accuracy: 0.9340 - precision: 0.9495 - recall: 0.9167 - auc: 0.9833 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1748 - tp: 110824.0000 - fp: 5900.0000 - tn: 114893.0000 - fn: 10047.0000 - accuracy: 0.9340 - precision: 0.9495 - recall: 0.9169 - auc: 0.9833 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1748 - tp: 113654.0000 - fp: 6046.0000 - tn: 117816.0000 - fn: 10292.0000 - accuracy: 0.9341 - precision: 0.9495 - recall: 0.9170 - auc: 0.9834 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.1746 - tp: 116481.0000 - fp: 6197.0000 - tn: 120739.0000 - fn: 10535.0000 - accuracy: 0.9341 - precision: 0.9495 - recall: 0.9171 - auc: 0.9834 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1745 - tp: 119290.0000 - fp: 6338.0000 - tn: 123688.0000 - fn: 10780.0000 - accuracy: 0.9342 - precision: 0.9495 - recall: 0.9171 - auc: 0.9834 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1744 - tp: 122175.0000 - fp: 6502.0000 - tn: 126551.0000 - fn: 11012.0000 - accuracy: 0.9342 - precision: 0.9495 - recall: 0.9173 - auc: 0.9834 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.1742 - tp: 124924.0000 - fp: 6638.0000 - tn: 129568.0000 - fn: 11254.0000 - accuracy: 0.9343 - precision: 0.9495 - recall: 0.9174 - auc: 0.9835 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/278 [=============>................] - ETA: 3s - loss: 0.1742 - tp: 127747.0000 - fp: 6817.0000 - tn: 132487.0000 - fn: 11477.0000 - accuracy: 0.9343 - precision: 0.9493 - recall: 0.9176 - auc: 0.9835 - prc: 0.9839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.1740 - tp: 130548.0000 - fp: 6973.0000 - tn: 135433.0000 - fn: 11718.0000 - accuracy: 0.9343 - precision: 0.9493 - recall: 0.9176 - auc: 0.9835 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 2s - loss: 0.1739 - tp: 133448.0000 - fp: 7108.0000 - tn: 138298.0000 - fn: 11962.0000 - accuracy: 0.9344 - precision: 0.9494 - recall: 0.9177 - auc: 0.9835 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "144/278 [==============>...............] - ETA: 2s - loss: 0.1738 - tp: 135380.0000 - fp: 7207.0000 - tn: 140199.0000 - fn: 12126.0000 - accuracy: 0.9344 - precision: 0.9495 - recall: 0.9178 - auc: 0.9835 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.1738 - tp: 137238.0000 - fp: 7315.0000 - tn: 142171.0000 - fn: 12284.0000 - accuracy: 0.9345 - precision: 0.9494 - recall: 0.9178 - auc: 0.9835 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1736 - tp: 139116.0000 - fp: 7411.0000 - tn: 144134.0000 - fn: 12443.0000 - accuracy: 0.9345 - precision: 0.9494 - recall: 0.9179 - auc: 0.9836 - prc: 0.9840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "150/278 [===============>..............] - ETA: 2s - loss: 0.1736 - tp: 141008.0000 - fp: 7512.0000 - tn: 146096.0000 - fn: 12584.0000 - accuracy: 0.9346 - precision: 0.9494 - recall: 0.9181 - auc: 0.9836 - prc: 0.9841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1735 - tp: 142862.0000 - fp: 7605.0000 - tn: 148076.0000 - fn: 12753.0000 - accuracy: 0.9346 - precision: 0.9495 - recall: 0.9180 - auc: 0.9836 - prc: 0.9841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1734 - tp: 144776.0000 - fp: 7709.0000 - tn: 149992.0000 - fn: 12915.0000 - accuracy: 0.9346 - precision: 0.9494 - recall: 0.9181 - auc: 0.9836 - prc: 0.9841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "156/278 [===============>..............] - ETA: 2s - loss: 0.1733 - tp: 146632.0000 - fp: 7819.0000 - tn: 151958.0000 - fn: 13079.0000 - accuracy: 0.9346 - precision: 0.9494 - recall: 0.9181 - auc: 0.9836 - prc: 0.9841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1731 - tp: 148544.0000 - fp: 7923.0000 - tn: 153892.0000 - fn: 13225.0000 - accuracy: 0.9346 - precision: 0.9494 - recall: 0.9182 - auc: 0.9837 - prc: 0.9841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1730 - tp: 151397.0000 - fp: 8061.0000 - tn: 156810.0000 - fn: 13460.0000 - accuracy: 0.9347 - precision: 0.9494 - recall: 0.9184 - auc: 0.9837 - prc: 0.9842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1729 - tp: 154254.0000 - fp: 8220.0000 - tn: 159726.0000 - fn: 13672.0000 - accuracy: 0.9348 - precision: 0.9494 - recall: 0.9186 - auc: 0.9837 - prc: 0.9842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1727 - tp: 157165.0000 - fp: 8379.0000 - tn: 162565.0000 - fn: 13907.0000 - accuracy: 0.9348 - precision: 0.9494 - recall: 0.9187 - auc: 0.9838 - prc: 0.9842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1726 - tp: 160001.0000 - fp: 8527.0000 - tn: 165505.0000 - fn: 14127.0000 - accuracy: 0.9349 - precision: 0.9494 - recall: 0.9189 - auc: 0.9838 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1725 - tp: 162870.0000 - fp: 8686.0000 - tn: 168401.0000 - fn: 14347.0000 - accuracy: 0.9350 - precision: 0.9494 - recall: 0.9190 - auc: 0.9838 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1723 - tp: 165711.0000 - fp: 8847.0000 - tn: 171309.0000 - fn: 14581.0000 - accuracy: 0.9350 - precision: 0.9493 - recall: 0.9191 - auc: 0.9838 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1723 - tp: 168553.0000 - fp: 8993.0000 - tn: 174213.0000 - fn: 14833.0000 - accuracy: 0.9350 - precision: 0.9493 - recall: 0.9191 - auc: 0.9838 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.1722 - tp: 171322.0000 - fp: 9143.0000 - tn: 177207.0000 - fn: 15064.0000 - accuracy: 0.9351 - precision: 0.9493 - recall: 0.9192 - auc: 0.9839 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.1721 - tp: 174233.0000 - fp: 9291.0000 - tn: 180073.0000 - fn: 15283.0000 - accuracy: 0.9351 - precision: 0.9494 - recall: 0.9194 - auc: 0.9839 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "188/278 [===================>..........] - ETA: 2s - loss: 0.1722 - tp: 177058.0000 - fp: 9455.0000 - tn: 182982.0000 - fn: 15529.0000 - accuracy: 0.9351 - precision: 0.9493 - recall: 0.9194 - auc: 0.9839 - prc: 0.9843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1719 - tp: 179971.0000 - fp: 9593.0000 - tn: 185842.0000 - fn: 15762.0000 - accuracy: 0.9352 - precision: 0.9494 - recall: 0.9195 - auc: 0.9839 - prc: 0.9844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1717 - tp: 182819.0000 - fp: 9728.0000 - tn: 188766.0000 - fn: 15999.0000 - accuracy: 0.9352 - precision: 0.9495 - recall: 0.9195 - auc: 0.9840 - prc: 0.9844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1717 - tp: 184679.0000 - fp: 9834.0000 - tn: 190748.0000 - fn: 16147.0000 - accuracy: 0.9353 - precision: 0.9494 - recall: 0.9196 - auc: 0.9840 - prc: 0.9844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1716 - tp: 187581.0000 - fp: 9993.0000 - tn: 193613.0000 - fn: 16365.0000 - accuracy: 0.9353 - precision: 0.9494 - recall: 0.9198 - auc: 0.9840 - prc: 0.9844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.1715 - tp: 190439.0000 - fp: 10130.0000 - tn: 196549.0000 - fn: 16578.0000 - accuracy: 0.9354 - precision: 0.9495 - recall: 0.9199 - auc: 0.9841 - prc: 0.9845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.1714 - tp: 193342.0000 - fp: 10289.0000 - tn: 199405.0000 - fn: 16804.0000 - accuracy: 0.9355 - precision: 0.9495 - recall: 0.9200 - auc: 0.9841 - prc: 0.9845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.1713 - tp: 196162.0000 - fp: 10431.0000 - tn: 202358.0000 - fn: 17033.0000 - accuracy: 0.9355 - precision: 0.9495 - recall: 0.9201 - auc: 0.9841 - prc: 0.9845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.1712 - tp: 199014.0000 - fp: 10586.0000 - tn: 205275.0000 - fn: 17253.0000 - accuracy: 0.9356 - precision: 0.9495 - recall: 0.9202 - auc: 0.9841 - prc: 0.9845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "214/278 [======================>.......] - ETA: 1s - loss: 0.1711 - tp: 201908.0000 - fp: 10746.0000 - tn: 208137.0000 - fn: 17481.0000 - accuracy: 0.9356 - precision: 0.9495 - recall: 0.9203 - auc: 0.9841 - prc: 0.9846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "216/278 [======================>.......] - ETA: 1s - loss: 0.1710 - tp: 203769.0000 - fp: 10837.0000 - tn: 210118.0000 - fn: 17644.0000 - accuracy: 0.9356 - precision: 0.9495 - recall: 0.9203 - auc: 0.9842 - prc: 0.9846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.1708 - tp: 206584.0000 - fp: 10975.0000 - tn: 213096.0000 - fn: 17857.0000 - accuracy: 0.9357 - precision: 0.9496 - recall: 0.9204 - auc: 0.9842 - prc: 0.9846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.1707 - tp: 209415.0000 - fp: 11132.0000 - tn: 216049.0000 - fn: 18060.0000 - accuracy: 0.9358 - precision: 0.9495 - recall: 0.9206 - auc: 0.9842 - prc: 0.9846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.1706 - tp: 212263.0000 - fp: 11282.0000 - tn: 218975.0000 - fn: 18280.0000 - accuracy: 0.9358 - precision: 0.9495 - recall: 0.9207 - auc: 0.9842 - prc: 0.9846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.1705 - tp: 215164.0000 - fp: 11440.0000 - tn: 221835.0000 - fn: 18505.0000 - accuracy: 0.9359 - precision: 0.9495 - recall: 0.9208 - auc: 0.9843 - prc: 0.9847"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "231/278 [=======================>......] - ETA: 1s - loss: 0.1703 - tp: 217998.0000 - fp: 11587.0000 - tn: 224770.0000 - fn: 18733.0000 - accuracy: 0.9359 - precision: 0.9495 - recall: 0.9209 - auc: 0.9843 - prc: 0.9847"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.1701 - tp: 220951.0000 - fp: 11735.0000 - tn: 227608.0000 - fn: 18938.0000 - accuracy: 0.9360 - precision: 0.9496 - recall: 0.9211 - auc: 0.9844 - prc: 0.9848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.1700 - tp: 223791.0000 - fp: 11894.0000 - tn: 230521.0000 - fn: 19170.0000 - accuracy: 0.9360 - precision: 0.9495 - recall: 0.9211 - auc: 0.9844 - prc: 0.9848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.1700 - tp: 226666.0000 - fp: 12055.0000 - tn: 233406.0000 - fn: 19393.0000 - accuracy: 0.9360 - precision: 0.9495 - recall: 0.9212 - auc: 0.9844 - prc: 0.9848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.1699 - tp: 229532.0000 - fp: 12210.0000 - tn: 236295.0000 - fn: 19627.0000 - accuracy: 0.9360 - precision: 0.9495 - recall: 0.9212 - auc: 0.9844 - prc: 0.9848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.1697 - tp: 232414.0000 - fp: 12354.0000 - tn: 239213.0000 - fn: 19827.0000 - accuracy: 0.9361 - precision: 0.9495 - recall: 0.9214 - auc: 0.9844 - prc: 0.9848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.1695 - tp: 235259.0000 - fp: 12509.0000 - tn: 242153.0000 - fn: 20031.0000 - accuracy: 0.9362 - precision: 0.9495 - recall: 0.9215 - auc: 0.9845 - prc: 0.9849"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1694 - tp: 238156.0000 - fp: 12645.0000 - tn: 245037.0000 - fn: 20258.0000 - accuracy: 0.9362 - precision: 0.9496 - recall: 0.9216 - auc: 0.9845 - prc: 0.9849"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1693 - tp: 240998.0000 - fp: 12793.0000 - tn: 247964.0000 - fn: 20485.0000 - accuracy: 0.9363 - precision: 0.9496 - recall: 0.9217 - auc: 0.9845 - prc: 0.9849"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1691 - tp: 243874.0000 - fp: 12953.0000 - tn: 250865.0000 - fn: 20692.0000 - accuracy: 0.9363 - precision: 0.9496 - recall: 0.9218 - auc: 0.9846 - prc: 0.9849"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1690 - tp: 246794.0000 - fp: 13112.0000 - tn: 253717.0000 - fn: 20905.0000 - accuracy: 0.9364 - precision: 0.9496 - recall: 0.9219 - auc: 0.9846 - prc: 0.9850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1689 - tp: 249650.0000 - fp: 13260.0000 - tn: 256639.0000 - fn: 21123.0000 - accuracy: 0.9364 - precision: 0.9496 - recall: 0.9220 - auc: 0.9846 - prc: 0.9850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1688 - tp: 252534.0000 - fp: 13409.0000 - tn: 259528.0000 - fn: 21345.0000 - accuracy: 0.9364 - precision: 0.9496 - recall: 0.9221 - auc: 0.9846 - prc: 0.9850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1686 - tp: 255430.0000 - fp: 13555.0000 - tn: 262415.0000 - fn: 21560.0000 - accuracy: 0.9365 - precision: 0.9496 - recall: 0.9222 - auc: 0.9847 - prc: 0.9850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1685 - tp: 258251.0000 - fp: 13706.0000 - tn: 265373.0000 - fn: 21774.0000 - accuracy: 0.9365 - precision: 0.9496 - recall: 0.9222 - auc: 0.9847 - prc: 0.9851"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1684 - tp: 261138.0000 - fp: 13858.0000 - tn: 268271.0000 - fn: 21981.0000 - accuracy: 0.9366 - precision: 0.9496 - recall: 0.9224 - auc: 0.9847 - prc: 0.9851"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.1683 - tp: 263076.0000 - fp: 13950.0000 - tn: 270190.0000 - fn: 22128.0000 - accuracy: 0.9366 - precision: 0.9496 - recall: 0.9224 - auc: 0.9847 - prc: 0.9851 - val_loss: 0.0677 - val_tp: 66.0000 - val_fp: 760.0000 - val_tn: 44740.0000 - val_fn: 3.0000 - val_accuracy: 0.9833 - val_precision: 0.0799 - val_recall: 0.9565 - val_auc: 0.9954 - val_prc: 0.7691\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1603 - tp: 962.0000 - fp: 60.0000 - tn: 958.0000 - fn: 68.0000 - accuracy: 0.9375 - precision: 0.9413 - recall: 0.9340 - auc: 0.9851 - prc: 0.9860"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1574 - tp: 4715.0000 - fp: 262.0000 - tn: 4912.0000 - fn: 351.0000 - accuracy: 0.9401 - precision: 0.9474 - recall: 0.9307 - auc: 0.9864 - prc: 0.9866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1565 - tp: 7549.0000 - fp: 421.0000 - tn: 7864.0000 - fn: 550.0000 - accuracy: 0.9407 - precision: 0.9472 - recall: 0.9321 - auc: 0.9868 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1564 - tp: 10428.0000 - fp: 566.0000 - tn: 10778.0000 - fn: 756.0000 - accuracy: 0.9413 - precision: 0.9485 - recall: 0.9324 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/278 [>.............................] - ETA: 5s - loss: 0.1557 - tp: 12308.0000 - fp: 675.0000 - tn: 12740.0000 - fn: 901.0000 - accuracy: 0.9408 - precision: 0.9480 - recall: 0.9318 - auc: 0.9870 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/278 [>.............................] - ETA: 5s - loss: 0.1561 - tp: 15144.0000 - fp: 815.0000 - tn: 15694.0000 - fn: 1115.0000 - accuracy: 0.9411 - precision: 0.9489 - recall: 0.9314 - auc: 0.9870 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/278 [=>............................] - ETA: 5s - loss: 0.1565 - tp: 18006.0000 - fp: 956.0000 - tn: 18628.0000 - fn: 1322.0000 - accuracy: 0.9415 - precision: 0.9496 - recall: 0.9316 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/278 [=>............................] - ETA: 5s - loss: 0.1563 - tp: 20935.0000 - fp: 1108.0000 - tn: 21508.0000 - fn: 1505.0000 - accuracy: 0.9420 - precision: 0.9497 - recall: 0.9329 - auc: 0.9870 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1570 - tp: 23867.0000 - fp: 1275.0000 - tn: 24369.0000 - fn: 1689.0000 - accuracy: 0.9421 - precision: 0.9493 - recall: 0.9339 - auc: 0.9869 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1567 - tp: 26757.0000 - fp: 1424.0000 - tn: 27270.0000 - fn: 1893.0000 - accuracy: 0.9422 - precision: 0.9495 - recall: 0.9339 - auc: 0.9869 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/278 [==>...........................] - ETA: 5s - loss: 0.1568 - tp: 29615.0000 - fp: 1583.0000 - tn: 30208.0000 - fn: 2082.0000 - accuracy: 0.9423 - precision: 0.9493 - recall: 0.9343 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.1568 - tp: 32486.0000 - fp: 1752.0000 - tn: 33104.0000 - fn: 2290.0000 - accuracy: 0.9420 - precision: 0.9488 - recall: 0.9341 - auc: 0.9869 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.1566 - tp: 35376.0000 - fp: 1896.0000 - tn: 36006.0000 - fn: 2498.0000 - accuracy: 0.9420 - precision: 0.9491 - recall: 0.9340 - auc: 0.9870 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/278 [===>..........................] - ETA: 5s - loss: 0.1569 - tp: 38256.0000 - fp: 2060.0000 - tn: 38917.0000 - fn: 2687.0000 - accuracy: 0.9421 - precision: 0.9489 - recall: 0.9344 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/278 [===>..........................] - ETA: 5s - loss: 0.1573 - tp: 41117.0000 - fp: 2247.0000 - tn: 41810.0000 - fn: 2890.0000 - accuracy: 0.9417 - precision: 0.9482 - recall: 0.9343 - auc: 0.9868 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/278 [===>..........................] - ETA: 5s - loss: 0.1571 - tp: 43972.0000 - fp: 2410.0000 - tn: 44728.0000 - fn: 3098.0000 - accuracy: 0.9415 - precision: 0.9480 - recall: 0.9342 - auc: 0.9868 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/278 [====>.........................] - ETA: 5s - loss: 0.1571 - tp: 46830.0000 - fp: 2586.0000 - tn: 47631.0000 - fn: 3305.0000 - accuracy: 0.9413 - precision: 0.9477 - recall: 0.9341 - auc: 0.9868 - prc: 0.9868"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/278 [====>.........................] - ETA: 4s - loss: 0.1571 - tp: 49722.0000 - fp: 2728.0000 - tn: 50541.0000 - fn: 3505.0000 - accuracy: 0.9415 - precision: 0.9480 - recall: 0.9341 - auc: 0.9868 - prc: 0.9868"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/278 [====>.........................] - ETA: 4s - loss: 0.1571 - tp: 52594.0000 - fp: 2889.0000 - tn: 53449.0000 - fn: 3708.0000 - accuracy: 0.9414 - precision: 0.9479 - recall: 0.9341 - auc: 0.9868 - prc: 0.9868"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/278 [=====>........................] - ETA: 4s - loss: 0.1572 - tp: 55440.0000 - fp: 3065.0000 - tn: 56379.0000 - fn: 3900.0000 - accuracy: 0.9414 - precision: 0.9476 - recall: 0.9343 - auc: 0.9867 - prc: 0.9868"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/278 [=====>........................] - ETA: 4s - loss: 0.1568 - tp: 58372.0000 - fp: 3208.0000 - tn: 59253.0000 - fn: 4095.0000 - accuracy: 0.9415 - precision: 0.9479 - recall: 0.9344 - auc: 0.9868 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 64/278 [=====>........................] - ETA: 4s - loss: 0.1567 - tp: 61243.0000 - fp: 3363.0000 - tn: 62165.0000 - fn: 4301.0000 - accuracy: 0.9415 - precision: 0.9479 - recall: 0.9344 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/278 [======>.......................] - ETA: 4s - loss: 0.1567 - tp: 64123.0000 - fp: 3515.0000 - tn: 65070.0000 - fn: 4508.0000 - accuracy: 0.9415 - precision: 0.9480 - recall: 0.9343 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/278 [======>.......................] - ETA: 4s - loss: 0.1567 - tp: 66018.0000 - fp: 3610.0000 - tn: 67056.0000 - fn: 4628.0000 - accuracy: 0.9417 - precision: 0.9482 - recall: 0.9345 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/278 [======>.......................] - ETA: 4s - loss: 0.1567 - tp: 68925.0000 - fp: 3775.0000 - tn: 69946.0000 - fn: 4810.0000 - accuracy: 0.9418 - precision: 0.9481 - recall: 0.9348 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/278 [=======>......................] - ETA: 4s - loss: 0.1565 - tp: 71749.0000 - fp: 3935.0000 - tn: 72903.0000 - fn: 5013.0000 - accuracy: 0.9417 - precision: 0.9480 - recall: 0.9347 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 78/278 [=======>......................] - ETA: 4s - loss: 0.1564 - tp: 74641.0000 - fp: 4083.0000 - tn: 75812.0000 - fn: 5208.0000 - accuracy: 0.9418 - precision: 0.9481 - recall: 0.9348 - auc: 0.9870 - prc: 0.9870"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/278 [=======>......................] - ETA: 4s - loss: 0.1564 - tp: 77511.0000 - fp: 4253.0000 - tn: 78712.0000 - fn: 5412.0000 - accuracy: 0.9417 - precision: 0.9480 - recall: 0.9347 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/278 [========>.....................] - ETA: 4s - loss: 0.1564 - tp: 80363.0000 - fp: 4416.0000 - tn: 81650.0000 - fn: 5603.0000 - accuracy: 0.9418 - precision: 0.9479 - recall: 0.9348 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 87/278 [========>.....................] - ETA: 4s - loss: 0.1563 - tp: 83225.0000 - fp: 4589.0000 - tn: 84564.0000 - fn: 5798.0000 - accuracy: 0.9417 - precision: 0.9477 - recall: 0.9349 - auc: 0.9869 - prc: 0.9869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 90/278 [========>.....................] - ETA: 4s - loss: 0.1562 - tp: 86151.0000 - fp: 4738.0000 - tn: 87455.0000 - fn: 5976.0000 - accuracy: 0.9419 - precision: 0.9479 - recall: 0.9351 - auc: 0.9870 - prc: 0.9870"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 93/278 [=========>....................] - ETA: 4s - loss: 0.1560 - tp: 89131.0000 - fp: 4873.0000 - tn: 90307.0000 - fn: 6153.0000 - accuracy: 0.9421 - precision: 0.9482 - recall: 0.9354 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/278 [=========>....................] - ETA: 4s - loss: 0.1558 - tp: 92014.0000 - fp: 5026.0000 - tn: 93213.0000 - fn: 6355.0000 - accuracy: 0.9421 - precision: 0.9482 - recall: 0.9354 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 99/278 [=========>....................] - ETA: 4s - loss: 0.1559 - tp: 94850.0000 - fp: 5213.0000 - tn: 96132.0000 - fn: 6557.0000 - accuracy: 0.9419 - precision: 0.9479 - recall: 0.9353 - auc: 0.9870 - prc: 0.9870"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "102/278 [==========>...................] - ETA: 3s - loss: 0.1558 - tp: 97706.0000 - fp: 5370.0000 - tn: 99076.0000 - fn: 6744.0000 - accuracy: 0.9420 - precision: 0.9479 - recall: 0.9354 - auc: 0.9870 - prc: 0.9870"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "105/278 [==========>...................] - ETA: 3s - loss: 0.1557 - tp: 100696.0000 - fp: 5522.0000 - tn: 101895.0000 - fn: 6927.0000 - accuracy: 0.9421 - precision: 0.9480 - recall: 0.9356 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "108/278 [==========>...................] - ETA: 3s - loss: 0.1557 - tp: 103622.0000 - fp: 5683.0000 - tn: 104765.0000 - fn: 7114.0000 - accuracy: 0.9421 - precision: 0.9480 - recall: 0.9358 - auc: 0.9870 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "111/278 [==========>...................] - ETA: 3s - loss: 0.1556 - tp: 106503.0000 - fp: 5845.0000 - tn: 107693.0000 - fn: 7287.0000 - accuracy: 0.9422 - precision: 0.9480 - recall: 0.9360 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "114/278 [===========>..................] - ETA: 3s - loss: 0.1556 - tp: 109394.0000 - fp: 6003.0000 - tn: 110606.0000 - fn: 7469.0000 - accuracy: 0.9423 - precision: 0.9480 - recall: 0.9361 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1554 - tp: 111299.0000 - fp: 6101.0000 - tn: 112575.0000 - fn: 7593.0000 - accuracy: 0.9424 - precision: 0.9480 - recall: 0.9361 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1553 - tp: 114177.0000 - fp: 6287.0000 - tn: 115467.0000 - fn: 7781.0000 - accuracy: 0.9423 - precision: 0.9478 - recall: 0.9362 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1552 - tp: 117055.0000 - fp: 6462.0000 - tn: 118386.0000 - fn: 7953.0000 - accuracy: 0.9423 - precision: 0.9477 - recall: 0.9364 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1551 - tp: 119950.0000 - fp: 6622.0000 - tn: 121280.0000 - fn: 8148.0000 - accuracy: 0.9423 - precision: 0.9477 - recall: 0.9364 - auc: 0.9871 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1552 - tp: 122801.0000 - fp: 6774.0000 - tn: 124231.0000 - fn: 8338.0000 - accuracy: 0.9424 - precision: 0.9477 - recall: 0.9364 - auc: 0.9871 - prc: 0.9871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1550 - tp: 125758.0000 - fp: 6923.0000 - tn: 127095.0000 - fn: 8512.0000 - accuracy: 0.9425 - precision: 0.9478 - recall: 0.9366 - auc: 0.9872 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 3s - loss: 0.1548 - tp: 128682.0000 - fp: 7082.0000 - tn: 129985.0000 - fn: 8683.0000 - accuracy: 0.9426 - precision: 0.9478 - recall: 0.9368 - auc: 0.9872 - prc: 0.9872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.1546 - tp: 131540.0000 - fp: 7242.0000 - tn: 132931.0000 - fn: 8863.0000 - accuracy: 0.9426 - precision: 0.9478 - recall: 0.9369 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.1546 - tp: 133482.0000 - fp: 7338.0000 - tn: 134854.0000 - fn: 8998.0000 - accuracy: 0.9426 - precision: 0.9479 - recall: 0.9368 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.1545 - tp: 136363.0000 - fp: 7486.0000 - tn: 137796.0000 - fn: 9171.0000 - accuracy: 0.9427 - precision: 0.9480 - recall: 0.9370 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 2s - loss: 0.1545 - tp: 139274.0000 - fp: 7648.0000 - tn: 140689.0000 - fn: 9349.0000 - accuracy: 0.9428 - precision: 0.9479 - recall: 0.9371 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1545 - tp: 142197.0000 - fp: 7825.0000 - tn: 143525.0000 - fn: 9557.0000 - accuracy: 0.9427 - precision: 0.9478 - recall: 0.9370 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1547 - tp: 145056.0000 - fp: 8013.0000 - tn: 146439.0000 - fn: 9740.0000 - accuracy: 0.9426 - precision: 0.9477 - recall: 0.9371 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1545 - tp: 147912.0000 - fp: 8182.0000 - tn: 149380.0000 - fn: 9918.0000 - accuracy: 0.9426 - precision: 0.9476 - recall: 0.9372 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.1545 - tp: 150823.0000 - fp: 8370.0000 - tn: 152246.0000 - fn: 10097.0000 - accuracy: 0.9426 - precision: 0.9474 - recall: 0.9373 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.1544 - tp: 153759.0000 - fp: 8529.0000 - tn: 155108.0000 - fn: 10284.0000 - accuracy: 0.9426 - precision: 0.9474 - recall: 0.9373 - auc: 0.9872 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.1544 - tp: 156695.0000 - fp: 8665.0000 - tn: 157996.0000 - fn: 10468.0000 - accuracy: 0.9427 - precision: 0.9476 - recall: 0.9374 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.1542 - tp: 159553.0000 - fp: 8816.0000 - tn: 160976.0000 - fn: 10623.0000 - accuracy: 0.9428 - precision: 0.9476 - recall: 0.9376 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.1541 - tp: 162423.0000 - fp: 8988.0000 - tn: 163893.0000 - fn: 10808.0000 - accuracy: 0.9428 - precision: 0.9476 - recall: 0.9376 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.1541 - tp: 165319.0000 - fp: 9161.0000 - tn: 166788.0000 - fn: 10988.0000 - accuracy: 0.9428 - precision: 0.9475 - recall: 0.9377 - auc: 0.9873 - prc: 0.9873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.1539 - tp: 168218.0000 - fp: 9314.0000 - tn: 169713.0000 - fn: 11155.0000 - accuracy: 0.9429 - precision: 0.9475 - recall: 0.9378 - auc: 0.9873 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.1539 - tp: 171075.0000 - fp: 9476.0000 - tn: 172670.0000 - fn: 11323.0000 - accuracy: 0.9429 - precision: 0.9475 - recall: 0.9379 - auc: 0.9873 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.1537 - tp: 173990.0000 - fp: 9629.0000 - tn: 175582.0000 - fn: 11487.0000 - accuracy: 0.9430 - precision: 0.9476 - recall: 0.9381 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/278 [==================>...........] - ETA: 2s - loss: 0.1536 - tp: 176849.0000 - fp: 9794.0000 - tn: 178528.0000 - fn: 11661.0000 - accuracy: 0.9431 - precision: 0.9475 - recall: 0.9381 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 2s - loss: 0.1536 - tp: 179732.0000 - fp: 9970.0000 - tn: 181421.0000 - fn: 11853.0000 - accuracy: 0.9430 - precision: 0.9474 - recall: 0.9381 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/278 [===================>..........] - ETA: 1s - loss: 0.1536 - tp: 182615.0000 - fp: 10150.0000 - tn: 184326.0000 - fn: 12029.0000 - accuracy: 0.9430 - precision: 0.9473 - recall: 0.9382 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.1535 - tp: 185548.0000 - fp: 10301.0000 - tn: 187205.0000 - fn: 12210.0000 - accuracy: 0.9430 - precision: 0.9474 - recall: 0.9383 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1534 - tp: 188403.0000 - fp: 10449.0000 - tn: 190169.0000 - fn: 12387.0000 - accuracy: 0.9431 - precision: 0.9475 - recall: 0.9383 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1533 - tp: 191313.0000 - fp: 10612.0000 - tn: 193072.0000 - fn: 12555.0000 - accuracy: 0.9432 - precision: 0.9474 - recall: 0.9384 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.1533 - tp: 194252.0000 - fp: 10780.0000 - tn: 195923.0000 - fn: 12741.0000 - accuracy: 0.9431 - precision: 0.9474 - recall: 0.9384 - auc: 0.9874 - prc: 0.9874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.1532 - tp: 197163.0000 - fp: 10947.0000 - tn: 198815.0000 - fn: 12915.0000 - accuracy: 0.9432 - precision: 0.9474 - recall: 0.9385 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.1532 - tp: 200081.0000 - fp: 11121.0000 - tn: 201690.0000 - fn: 13092.0000 - accuracy: 0.9432 - precision: 0.9473 - recall: 0.9386 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.1532 - tp: 203004.0000 - fp: 11289.0000 - tn: 204588.0000 - fn: 13247.0000 - accuracy: 0.9432 - precision: 0.9473 - recall: 0.9387 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "214/278 [======================>.......] - ETA: 1s - loss: 0.1531 - tp: 205919.0000 - fp: 11472.0000 - tn: 207459.0000 - fn: 13422.0000 - accuracy: 0.9432 - precision: 0.9472 - recall: 0.9388 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "217/278 [======================>.......] - ETA: 1s - loss: 0.1530 - tp: 208806.0000 - fp: 11644.0000 - tn: 210368.0000 - fn: 13598.0000 - accuracy: 0.9432 - precision: 0.9472 - recall: 0.9389 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "220/278 [======================>.......] - ETA: 1s - loss: 0.1530 - tp: 211745.0000 - fp: 11805.0000 - tn: 213245.0000 - fn: 13765.0000 - accuracy: 0.9432 - precision: 0.9472 - recall: 0.9390 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "223/278 [=======================>......] - ETA: 1s - loss: 0.1528 - tp: 214651.0000 - fp: 11945.0000 - tn: 216169.0000 - fn: 13939.0000 - accuracy: 0.9433 - precision: 0.9473 - recall: 0.9390 - auc: 0.9875 - prc: 0.9875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "226/278 [=======================>......] - ETA: 1s - loss: 0.1527 - tp: 217660.0000 - fp: 12106.0000 - tn: 218971.0000 - fn: 14111.0000 - accuracy: 0.9434 - precision: 0.9473 - recall: 0.9391 - auc: 0.9875 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.1526 - tp: 220628.0000 - fp: 12257.0000 - tn: 221822.0000 - fn: 14285.0000 - accuracy: 0.9434 - precision: 0.9474 - recall: 0.9392 - auc: 0.9875 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.1525 - tp: 223506.0000 - fp: 12404.0000 - tn: 224767.0000 - fn: 14459.0000 - accuracy: 0.9435 - precision: 0.9474 - recall: 0.9392 - auc: 0.9876 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1524 - tp: 226432.0000 - fp: 12562.0000 - tn: 227665.0000 - fn: 14621.0000 - accuracy: 0.9435 - precision: 0.9474 - recall: 0.9393 - auc: 0.9876 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.1523 - tp: 228357.0000 - fp: 12664.0000 - tn: 229626.0000 - fn: 14729.0000 - accuracy: 0.9436 - precision: 0.9475 - recall: 0.9394 - auc: 0.9876 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.1522 - tp: 231235.0000 - fp: 12837.0000 - tn: 232555.0000 - fn: 14893.0000 - accuracy: 0.9436 - precision: 0.9474 - recall: 0.9395 - auc: 0.9876 - prc: 0.9876"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.1521 - tp: 234129.0000 - fp: 12976.0000 - tn: 235494.0000 - fn: 15065.0000 - accuracy: 0.9437 - precision: 0.9475 - recall: 0.9395 - auc: 0.9876 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.1521 - tp: 236920.0000 - fp: 13157.0000 - tn: 238526.0000 - fn: 15205.0000 - accuracy: 0.9437 - precision: 0.9474 - recall: 0.9397 - auc: 0.9876 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.1520 - tp: 239823.0000 - fp: 13316.0000 - tn: 241441.0000 - fn: 15372.0000 - accuracy: 0.9437 - precision: 0.9474 - recall: 0.9398 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1519 - tp: 242764.0000 - fp: 13490.0000 - tn: 244330.0000 - fn: 15512.0000 - accuracy: 0.9438 - precision: 0.9474 - recall: 0.9399 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1518 - tp: 245635.0000 - fp: 13661.0000 - tn: 247259.0000 - fn: 15685.0000 - accuracy: 0.9438 - precision: 0.9473 - recall: 0.9400 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1517 - tp: 248584.0000 - fp: 13815.0000 - tn: 250141.0000 - fn: 15844.0000 - accuracy: 0.9439 - precision: 0.9474 - recall: 0.9401 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1517 - tp: 251483.0000 - fp: 14018.0000 - tn: 253018.0000 - fn: 16009.0000 - accuracy: 0.9438 - precision: 0.9472 - recall: 0.9402 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1516 - tp: 254368.0000 - fp: 14214.0000 - tn: 255915.0000 - fn: 16175.0000 - accuracy: 0.9438 - precision: 0.9471 - recall: 0.9402 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1515 - tp: 257209.0000 - fp: 14360.0000 - tn: 258920.0000 - fn: 16327.0000 - accuracy: 0.9439 - precision: 0.9471 - recall: 0.9403 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1515 - tp: 260137.0000 - fp: 14527.0000 - tn: 261807.0000 - fn: 16489.0000 - accuracy: 0.9439 - precision: 0.9471 - recall: 0.9404 - auc: 0.9877 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1514 - tp: 263035.0000 - fp: 14692.0000 - tn: 264730.0000 - fn: 16647.0000 - accuracy: 0.9439 - precision: 0.9471 - recall: 0.9405 - auc: 0.9878 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1513 - tp: 265963.0000 - fp: 14872.0000 - tn: 267604.0000 - fn: 16809.0000 - accuracy: 0.9440 - precision: 0.9470 - recall: 0.9406 - auc: 0.9878 - prc: 0.9877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.1513 - tp: 267889.0000 - fp: 14968.0000 - tn: 269576.0000 - fn: 16911.0000 - accuracy: 0.9440 - precision: 0.9471 - recall: 0.9406 - auc: 0.9878 - prc: 0.9878 - val_loss: 0.0582 - val_tp: 66.0000 - val_fp: 747.0000 - val_tn: 44753.0000 - val_fn: 3.0000 - val_accuracy: 0.9835 - val_precision: 0.0812 - val_recall: 0.9565 - val_auc: 0.9957 - val_prc: 0.7716\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1499 - tp: 977.0000 - fp: 65.0000 - tn: 956.0000 - fn: 50.0000 - accuracy: 0.9438 - precision: 0.9376 - recall: 0.9513 - auc: 0.9875 - prc: 0.9878"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1399 - tp: 4845.0000 - fp: 285.0000 - tn: 4869.0000 - fn: 241.0000 - accuracy: 0.9486 - precision: 0.9444 - recall: 0.9526 - auc: 0.9894 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1413 - tp: 7804.0000 - fp: 443.0000 - tn: 7738.0000 - fn: 399.0000 - accuracy: 0.9486 - precision: 0.9463 - recall: 0.9514 - auc: 0.9893 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1415 - tp: 10744.0000 - fp: 602.0000 - tn: 10642.0000 - fn: 540.0000 - accuracy: 0.9493 - precision: 0.9469 - recall: 0.9521 - auc: 0.9893 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1411 - tp: 13697.0000 - fp: 755.0000 - tn: 13531.0000 - fn: 689.0000 - accuracy: 0.9496 - precision: 0.9478 - recall: 0.9521 - auc: 0.9893 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1419 - tp: 16646.0000 - fp: 915.0000 - tn: 16397.0000 - fn: 858.0000 - accuracy: 0.9491 - precision: 0.9479 - recall: 0.9510 - auc: 0.9892 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1422 - tp: 19635.0000 - fp: 1073.0000 - tn: 19251.0000 - fn: 1001.0000 - accuracy: 0.9494 - precision: 0.9482 - recall: 0.9515 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1419 - tp: 22564.0000 - fp: 1241.0000 - tn: 22154.0000 - fn: 1145.0000 - accuracy: 0.9493 - precision: 0.9479 - recall: 0.9517 - auc: 0.9892 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.1414 - tp: 25520.0000 - fp: 1390.0000 - tn: 25039.0000 - fn: 1299.0000 - accuracy: 0.9495 - precision: 0.9483 - recall: 0.9516 - auc: 0.9893 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.1419 - tp: 28445.0000 - fp: 1554.0000 - tn: 27930.0000 - fn: 1463.0000 - accuracy: 0.9492 - precision: 0.9482 - recall: 0.9511 - auc: 0.9892 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.1421 - tp: 31367.0000 - fp: 1742.0000 - tn: 30823.0000 - fn: 1604.0000 - accuracy: 0.9489 - precision: 0.9474 - recall: 0.9514 - auc: 0.9891 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/278 [==>...........................] - ETA: 5s - loss: 0.1419 - tp: 34287.0000 - fp: 1908.0000 - tn: 33727.0000 - fn: 1758.0000 - accuracy: 0.9489 - precision: 0.9473 - recall: 0.9512 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/278 [===>..........................] - ETA: 5s - loss: 0.1419 - tp: 37144.0000 - fp: 2080.0000 - tn: 36693.0000 - fn: 1907.0000 - accuracy: 0.9488 - precision: 0.9470 - recall: 0.9512 - auc: 0.9891 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 5s - loss: 0.1418 - tp: 40067.0000 - fp: 2232.0000 - tn: 39607.0000 - fn: 2062.0000 - accuracy: 0.9489 - precision: 0.9472 - recall: 0.9511 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/278 [===>..........................] - ETA: 5s - loss: 0.1412 - tp: 42987.0000 - fp: 2358.0000 - tn: 42566.0000 - fn: 2201.0000 - accuracy: 0.9494 - precision: 0.9480 - recall: 0.9513 - auc: 0.9893 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/278 [====>.........................] - ETA: 5s - loss: 0.1412 - tp: 45845.0000 - fp: 2530.0000 - tn: 45529.0000 - fn: 2352.0000 - accuracy: 0.9493 - precision: 0.9477 - recall: 0.9512 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 5s - loss: 0.1415 - tp: 48778.0000 - fp: 2703.0000 - tn: 48410.0000 - fn: 2509.0000 - accuracy: 0.9491 - precision: 0.9475 - recall: 0.9511 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.1416 - tp: 51715.0000 - fp: 2879.0000 - tn: 51288.0000 - fn: 2662.0000 - accuracy: 0.9490 - precision: 0.9473 - recall: 0.9510 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1421 - tp: 54633.0000 - fp: 3057.0000 - tn: 54183.0000 - fn: 2815.0000 - accuracy: 0.9488 - precision: 0.9470 - recall: 0.9510 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1424 - tp: 57506.0000 - fp: 3234.0000 - tn: 57112.0000 - fn: 2980.0000 - accuracy: 0.9486 - precision: 0.9468 - recall: 0.9507 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1423 - tp: 60500.0000 - fp: 3403.0000 - tn: 59967.0000 - fn: 3106.0000 - accuracy: 0.9487 - precision: 0.9467 - recall: 0.9512 - auc: 0.9891 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 64/278 [=====>........................] - ETA: 4s - loss: 0.1421 - tp: 62461.0000 - fp: 3502.0000 - tn: 61906.0000 - fn: 3203.0000 - accuracy: 0.9488 - precision: 0.9469 - recall: 0.9512 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/278 [======>.......................] - ETA: 4s - loss: 0.1426 - tp: 65424.0000 - fp: 3688.0000 - tn: 64750.0000 - fn: 3354.0000 - accuracy: 0.9487 - precision: 0.9466 - recall: 0.9512 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/278 [======>.......................] - ETA: 4s - loss: 0.1428 - tp: 68317.0000 - fp: 3870.0000 - tn: 67668.0000 - fn: 3505.0000 - accuracy: 0.9486 - precision: 0.9464 - recall: 0.9512 - auc: 0.9890 - prc: 0.9889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/278 [======>.......................] - ETA: 4s - loss: 0.1428 - tp: 71261.0000 - fp: 4057.0000 - tn: 70543.0000 - fn: 3643.0000 - accuracy: 0.9485 - precision: 0.9461 - recall: 0.9514 - auc: 0.9890 - prc: 0.9889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 76/278 [=======>......................] - ETA: 4s - loss: 0.1427 - tp: 74199.0000 - fp: 4221.0000 - tn: 73445.0000 - fn: 3783.0000 - accuracy: 0.9486 - precision: 0.9462 - recall: 0.9515 - auc: 0.9890 - prc: 0.9889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 0.1426 - tp: 77128.0000 - fp: 4367.0000 - tn: 76375.0000 - fn: 3922.0000 - accuracy: 0.9488 - precision: 0.9464 - recall: 0.9516 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/278 [=======>......................] - ETA: 4s - loss: 0.1426 - tp: 80059.0000 - fp: 4521.0000 - tn: 79297.0000 - fn: 4059.0000 - accuracy: 0.9489 - precision: 0.9465 - recall: 0.9517 - auc: 0.9891 - prc: 0.9889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 0.1425 - tp: 83050.0000 - fp: 4677.0000 - tn: 82147.0000 - fn: 4206.0000 - accuracy: 0.9490 - precision: 0.9467 - recall: 0.9518 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/278 [========>.....................] - ETA: 4s - loss: 0.1423 - tp: 85913.0000 - fp: 4821.0000 - tn: 85138.0000 - fn: 4352.0000 - accuracy: 0.9491 - precision: 0.9469 - recall: 0.9518 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/278 [========>.....................] - ETA: 4s - loss: 0.1423 - tp: 88862.0000 - fp: 4988.0000 - tn: 88019.0000 - fn: 4499.0000 - accuracy: 0.9491 - precision: 0.9469 - recall: 0.9518 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/278 [=========>....................] - ETA: 4s - loss: 0.1421 - tp: 91808.0000 - fp: 5156.0000 - tn: 90908.0000 - fn: 4640.0000 - accuracy: 0.9491 - precision: 0.9468 - recall: 0.9519 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 4s - loss: 0.1421 - tp: 94708.0000 - fp: 5314.0000 - tn: 93850.0000 - fn: 4784.0000 - accuracy: 0.9492 - precision: 0.9469 - recall: 0.9519 - auc: 0.9892 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 3s - loss: 0.1420 - tp: 97635.0000 - fp: 5485.0000 - tn: 96764.0000 - fn: 4916.0000 - accuracy: 0.9492 - precision: 0.9468 - recall: 0.9521 - auc: 0.9892 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 0.1421 - tp: 100598.0000 - fp: 5684.0000 - tn: 99606.0000 - fn: 5056.0000 - accuracy: 0.9491 - precision: 0.9465 - recall: 0.9521 - auc: 0.9891 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.1420 - tp: 103519.0000 - fp: 5833.0000 - tn: 102526.0000 - fn: 5210.0000 - accuracy: 0.9491 - precision: 0.9467 - recall: 0.9521 - auc: 0.9892 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.1418 - tp: 106448.0000 - fp: 5988.0000 - tn: 105432.0000 - fn: 5364.0000 - accuracy: 0.9491 - precision: 0.9467 - recall: 0.9520 - auc: 0.9892 - prc: 0.9890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.1417 - tp: 109466.0000 - fp: 6140.0000 - tn: 108266.0000 - fn: 5504.0000 - accuracy: 0.9492 - precision: 0.9469 - recall: 0.9521 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.1417 - tp: 112429.0000 - fp: 6300.0000 - tn: 111144.0000 - fn: 5647.0000 - accuracy: 0.9493 - precision: 0.9469 - recall: 0.9522 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1416 - tp: 115388.0000 - fp: 6458.0000 - tn: 114030.0000 - fn: 5788.0000 - accuracy: 0.9493 - precision: 0.9470 - recall: 0.9522 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1416 - tp: 118334.0000 - fp: 6622.0000 - tn: 116915.0000 - fn: 5937.0000 - accuracy: 0.9493 - precision: 0.9470 - recall: 0.9522 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "123/278 [============>.................] - ETA: 3s - loss: 0.1416 - tp: 120303.0000 - fp: 6728.0000 - tn: 118844.0000 - fn: 6029.0000 - accuracy: 0.9494 - precision: 0.9470 - recall: 0.9523 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1416 - tp: 122287.0000 - fp: 6844.0000 - tn: 120757.0000 - fn: 6112.0000 - accuracy: 0.9494 - precision: 0.9470 - recall: 0.9524 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1416 - tp: 125229.0000 - fp: 7011.0000 - tn: 123660.0000 - fn: 6244.0000 - accuracy: 0.9494 - precision: 0.9470 - recall: 0.9525 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1415 - tp: 128176.0000 - fp: 7186.0000 - tn: 126541.0000 - fn: 6385.0000 - accuracy: 0.9494 - precision: 0.9469 - recall: 0.9525 - auc: 0.9892 - prc: 0.9891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 3s - loss: 0.1414 - tp: 131120.0000 - fp: 7331.0000 - tn: 129462.0000 - fn: 6519.0000 - accuracy: 0.9495 - precision: 0.9470 - recall: 0.9526 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.1412 - tp: 134080.0000 - fp: 7492.0000 - tn: 132358.0000 - fn: 6646.0000 - accuracy: 0.9496 - precision: 0.9471 - recall: 0.9528 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/278 [==============>...............] - ETA: 3s - loss: 0.1414 - tp: 136987.0000 - fp: 7671.0000 - tn: 135274.0000 - fn: 6788.0000 - accuracy: 0.9496 - precision: 0.9470 - recall: 0.9528 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "143/278 [==============>...............] - ETA: 3s - loss: 0.1413 - tp: 139911.0000 - fp: 7854.0000 - tn: 138170.0000 - fn: 6929.0000 - accuracy: 0.9495 - precision: 0.9468 - recall: 0.9528 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.1413 - tp: 142889.0000 - fp: 8038.0000 - tn: 141016.0000 - fn: 7065.0000 - accuracy: 0.9495 - precision: 0.9467 - recall: 0.9529 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.1412 - tp: 145855.0000 - fp: 8219.0000 - tn: 143883.0000 - fn: 7195.0000 - accuracy: 0.9495 - precision: 0.9467 - recall: 0.9530 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1412 - tp: 148800.0000 - fp: 8383.0000 - tn: 146777.0000 - fn: 7336.0000 - accuracy: 0.9495 - precision: 0.9467 - recall: 0.9530 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1410 - tp: 151836.0000 - fp: 8537.0000 - tn: 149600.0000 - fn: 7467.0000 - accuracy: 0.9496 - precision: 0.9468 - recall: 0.9531 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1410 - tp: 154730.0000 - fp: 8698.0000 - tn: 152560.0000 - fn: 7596.0000 - accuracy: 0.9496 - precision: 0.9468 - recall: 0.9532 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1411 - tp: 157642.0000 - fp: 8889.0000 - tn: 155455.0000 - fn: 7742.0000 - accuracy: 0.9496 - precision: 0.9466 - recall: 0.9532 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1410 - tp: 160550.0000 - fp: 9043.0000 - tn: 158414.0000 - fn: 7865.0000 - accuracy: 0.9497 - precision: 0.9467 - recall: 0.9533 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1410 - tp: 163474.0000 - fp: 9215.0000 - tn: 161327.0000 - fn: 8000.0000 - accuracy: 0.9497 - precision: 0.9466 - recall: 0.9533 - auc: 0.9893 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1408 - tp: 166424.0000 - fp: 9377.0000 - tn: 164223.0000 - fn: 8136.0000 - accuracy: 0.9497 - precision: 0.9467 - recall: 0.9534 - auc: 0.9894 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1408 - tp: 169383.0000 - fp: 9542.0000 - tn: 167122.0000 - fn: 8257.0000 - accuracy: 0.9498 - precision: 0.9467 - recall: 0.9535 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1407 - tp: 172345.0000 - fp: 9716.0000 - tn: 170002.0000 - fn: 8385.0000 - accuracy: 0.9498 - precision: 0.9466 - recall: 0.9536 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1407 - tp: 175288.0000 - fp: 9886.0000 - tn: 172899.0000 - fn: 8519.0000 - accuracy: 0.9498 - precision: 0.9466 - recall: 0.9537 - auc: 0.9894 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.1406 - tp: 178290.0000 - fp: 10053.0000 - tn: 175736.0000 - fn: 8657.0000 - accuracy: 0.9498 - precision: 0.9466 - recall: 0.9537 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.1407 - tp: 181178.0000 - fp: 10242.0000 - tn: 178675.0000 - fn: 8785.0000 - accuracy: 0.9498 - precision: 0.9465 - recall: 0.9538 - auc: 0.9894 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "188/278 [===================>..........] - ETA: 2s - loss: 0.1406 - tp: 184070.0000 - fp: 10399.0000 - tn: 181645.0000 - fn: 8910.0000 - accuracy: 0.9498 - precision: 0.9465 - recall: 0.9538 - auc: 0.9894 - prc: 0.9892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1405 - tp: 187049.0000 - fp: 10564.0000 - tn: 184512.0000 - fn: 9043.0000 - accuracy: 0.9499 - precision: 0.9465 - recall: 0.9539 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1404 - tp: 190005.0000 - fp: 10714.0000 - tn: 187422.0000 - fn: 9171.0000 - accuracy: 0.9500 - precision: 0.9466 - recall: 0.9540 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.1404 - tp: 192988.0000 - fp: 10884.0000 - tn: 190282.0000 - fn: 9302.0000 - accuracy: 0.9500 - precision: 0.9466 - recall: 0.9540 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.1403 - tp: 195863.0000 - fp: 11054.0000 - tn: 193254.0000 - fn: 9429.0000 - accuracy: 0.9500 - precision: 0.9466 - recall: 0.9541 - auc: 0.9894 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.1401 - tp: 198844.0000 - fp: 11202.0000 - tn: 196137.0000 - fn: 9561.0000 - accuracy: 0.9501 - precision: 0.9467 - recall: 0.9541 - auc: 0.9895 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.1401 - tp: 201793.0000 - fp: 11380.0000 - tn: 199028.0000 - fn: 9687.0000 - accuracy: 0.9501 - precision: 0.9466 - recall: 0.9542 - auc: 0.9895 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1400 - tp: 204741.0000 - fp: 11540.0000 - tn: 201946.0000 - fn: 9805.0000 - accuracy: 0.9501 - precision: 0.9466 - recall: 0.9543 - auc: 0.9895 - prc: 0.9893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1398 - tp: 207728.0000 - fp: 11712.0000 - tn: 204805.0000 - fn: 9931.0000 - accuracy: 0.9502 - precision: 0.9466 - recall: 0.9544 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1398 - tp: 210631.0000 - fp: 11895.0000 - tn: 207731.0000 - fn: 10063.0000 - accuracy: 0.9501 - precision: 0.9465 - recall: 0.9544 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1396 - tp: 213516.0000 - fp: 12074.0000 - tn: 210700.0000 - fn: 10174.0000 - accuracy: 0.9502 - precision: 0.9465 - recall: 0.9545 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.1397 - tp: 216421.0000 - fp: 12272.0000 - tn: 213620.0000 - fn: 10295.0000 - accuracy: 0.9501 - precision: 0.9463 - recall: 0.9546 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/278 [=======================>......] - ETA: 1s - loss: 0.1397 - tp: 219370.0000 - fp: 12452.0000 - tn: 216506.0000 - fn: 10424.0000 - accuracy: 0.9501 - precision: 0.9463 - recall: 0.9546 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "227/278 [=======================>......] - ETA: 1s - loss: 0.1396 - tp: 222333.0000 - fp: 12598.0000 - tn: 219418.0000 - fn: 10547.0000 - accuracy: 0.9502 - precision: 0.9464 - recall: 0.9547 - auc: 0.9895 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.1394 - tp: 224248.0000 - fp: 12684.0000 - tn: 221436.0000 - fn: 10624.0000 - accuracy: 0.9503 - precision: 0.9465 - recall: 0.9548 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.1394 - tp: 227186.0000 - fp: 12875.0000 - tn: 224322.0000 - fn: 10753.0000 - accuracy: 0.9503 - precision: 0.9464 - recall: 0.9548 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1394 - tp: 230183.0000 - fp: 13052.0000 - tn: 227174.0000 - fn: 10871.0000 - accuracy: 0.9503 - precision: 0.9463 - recall: 0.9549 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1392 - tp: 233070.0000 - fp: 13201.0000 - tn: 230168.0000 - fn: 10985.0000 - accuracy: 0.9504 - precision: 0.9464 - recall: 0.9550 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.1391 - tp: 236030.0000 - fp: 13366.0000 - tn: 233040.0000 - fn: 11132.0000 - accuracy: 0.9504 - precision: 0.9464 - recall: 0.9550 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1391 - tp: 238926.0000 - fp: 13543.0000 - tn: 236004.0000 - fn: 11239.0000 - accuracy: 0.9504 - precision: 0.9464 - recall: 0.9551 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.1390 - tp: 241930.0000 - fp: 13724.0000 - tn: 238842.0000 - fn: 11360.0000 - accuracy: 0.9504 - precision: 0.9463 - recall: 0.9552 - auc: 0.9896 - prc: 0.9894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.1390 - tp: 244927.0000 - fp: 13897.0000 - tn: 241692.0000 - fn: 11484.0000 - accuracy: 0.9504 - precision: 0.9463 - recall: 0.9552 - auc: 0.9896 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "253/278 [==========================>...] - ETA: 0s - loss: 0.1389 - tp: 247846.0000 - fp: 14062.0000 - tn: 244627.0000 - fn: 11609.0000 - accuracy: 0.9505 - precision: 0.9463 - recall: 0.9553 - auc: 0.9896 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "256/278 [==========================>...] - ETA: 0s - loss: 0.1389 - tp: 250704.0000 - fp: 14233.0000 - tn: 247613.0000 - fn: 11738.0000 - accuracy: 0.9505 - precision: 0.9463 - recall: 0.9553 - auc: 0.9896 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "259/278 [==========================>...] - ETA: 0s - loss: 0.1388 - tp: 253634.0000 - fp: 14401.0000 - tn: 250534.0000 - fn: 11863.0000 - accuracy: 0.9505 - precision: 0.9463 - recall: 0.9553 - auc: 0.9896 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "262/278 [===========================>..] - ETA: 0s - loss: 0.1387 - tp: 256586.0000 - fp: 14574.0000 - tn: 253418.0000 - fn: 11998.0000 - accuracy: 0.9505 - precision: 0.9463 - recall: 0.9553 - auc: 0.9896 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "265/278 [===========================>..] - ETA: 0s - loss: 0.1386 - tp: 259527.0000 - fp: 14728.0000 - tn: 256352.0000 - fn: 12113.0000 - accuracy: 0.9505 - precision: 0.9463 - recall: 0.9554 - auc: 0.9897 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "268/278 [===========================>..] - ETA: 0s - loss: 0.1386 - tp: 262469.0000 - fp: 14893.0000 - tn: 259273.0000 - fn: 12229.0000 - accuracy: 0.9506 - precision: 0.9463 - recall: 0.9555 - auc: 0.9897 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "271/278 [============================>.] - ETA: 0s - loss: 0.1385 - tp: 265397.0000 - fp: 15057.0000 - tn: 262201.0000 - fn: 12353.0000 - accuracy: 0.9506 - precision: 0.9463 - recall: 0.9555 - auc: 0.9897 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "274/278 [============================>.] - ETA: 0s - loss: 0.1384 - tp: 268363.0000 - fp: 15226.0000 - tn: 265091.0000 - fn: 12472.0000 - accuracy: 0.9506 - precision: 0.9463 - recall: 0.9556 - auc: 0.9897 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "277/278 [============================>.] - ETA: 0s - loss: 0.1383 - tp: 271302.0000 - fp: 15396.0000 - tn: 268015.0000 - fn: 12583.0000 - accuracy: 0.9507 - precision: 0.9463 - recall: 0.9557 - auc: 0.9897 - prc: 0.9895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.1383 - tp: 272263.0000 - fp: 15458.0000 - tn: 269001.0000 - fn: 12622.0000 - accuracy: 0.9507 - precision: 0.9463 - recall: 0.9557 - auc: 0.9897 - prc: 0.9895 - val_loss: 0.0514 - val_tp: 66.0000 - val_fp: 716.0000 - val_tn: 44784.0000 - val_fn: 3.0000 - val_accuracy: 0.9842 - val_precision: 0.0844 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7749\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1251 - tp: 1003.0000 - fp: 50.0000 - tn: 952.0000 - fn: 43.0000 - accuracy: 0.9546 - precision: 0.9525 - recall: 0.9589 - auc: 0.9917 - prc: 0.9920"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/278 [..............................] - ETA: 4s - loss: 0.1303 - tp: 3960.0000 - fp: 221.0000 - tn: 3841.0000 - fn: 170.0000 - accuracy: 0.9523 - precision: 0.9471 - recall: 0.9588 - auc: 0.9906 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/278 [..............................] - ETA: 5s - loss: 0.1312 - tp: 6897.0000 - fp: 397.0000 - tn: 6739.0000 - fn: 303.0000 - accuracy: 0.9512 - precision: 0.9456 - recall: 0.9579 - auc: 0.9906 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/278 [>.............................] - ETA: 5s - loss: 0.1319 - tp: 9880.0000 - fp: 574.0000 - tn: 9597.0000 - fn: 429.0000 - accuracy: 0.9510 - precision: 0.9451 - recall: 0.9584 - auc: 0.9905 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 12/278 [>.............................] - ETA: 5s - loss: 0.1329 - tp: 11813.0000 - fp: 676.0000 - tn: 11575.0000 - fn: 512.0000 - accuracy: 0.9517 - precision: 0.9459 - recall: 0.9585 - auc: 0.9905 - prc: 0.9903"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/278 [>.............................] - ETA: 5s - loss: 0.1314 - tp: 14791.0000 - fp: 818.0000 - tn: 14480.0000 - fn: 631.0000 - accuracy: 0.9528 - precision: 0.9476 - recall: 0.9591 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/278 [>.............................] - ETA: 5s - loss: 0.1318 - tp: 17766.0000 - fp: 991.0000 - tn: 17348.0000 - fn: 759.0000 - accuracy: 0.9525 - precision: 0.9472 - recall: 0.9590 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/278 [=>............................] - ETA: 5s - loss: 0.1316 - tp: 20678.0000 - fp: 1154.0000 - tn: 20278.0000 - fn: 898.0000 - accuracy: 0.9523 - precision: 0.9471 - recall: 0.9584 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/278 [=>............................] - ETA: 5s - loss: 0.1315 - tp: 23646.0000 - fp: 1328.0000 - tn: 23171.0000 - fn: 1007.0000 - accuracy: 0.9525 - precision: 0.9468 - recall: 0.9592 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/278 [=>............................] - ETA: 5s - loss: 0.1316 - tp: 26591.0000 - fp: 1498.0000 - tn: 26074.0000 - fn: 1133.0000 - accuracy: 0.9524 - precision: 0.9467 - recall: 0.9591 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/278 [==>...........................] - ETA: 5s - loss: 0.1315 - tp: 29490.0000 - fp: 1675.0000 - tn: 29026.0000 - fn: 1249.0000 - accuracy: 0.9524 - precision: 0.9463 - recall: 0.9594 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 33/278 [==>...........................] - ETA: 5s - loss: 0.1311 - tp: 32402.0000 - fp: 1829.0000 - tn: 31992.0000 - fn: 1361.0000 - accuracy: 0.9528 - precision: 0.9466 - recall: 0.9597 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/278 [==>...........................] - ETA: 5s - loss: 0.1308 - tp: 34363.0000 - fp: 1934.0000 - tn: 33943.0000 - fn: 1440.0000 - accuracy: 0.9529 - precision: 0.9467 - recall: 0.9598 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/278 [===>..........................] - ETA: 5s - loss: 0.1311 - tp: 37375.0000 - fp: 2120.0000 - tn: 36770.0000 - fn: 1559.0000 - accuracy: 0.9527 - precision: 0.9463 - recall: 0.9600 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 5s - loss: 0.1315 - tp: 40287.0000 - fp: 2300.0000 - tn: 39699.0000 - fn: 1682.0000 - accuracy: 0.9526 - precision: 0.9460 - recall: 0.9599 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/278 [===>..........................] - ETA: 5s - loss: 0.1312 - tp: 43251.0000 - fp: 2462.0000 - tn: 42602.0000 - fn: 1797.0000 - accuracy: 0.9527 - precision: 0.9461 - recall: 0.9601 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/278 [====>.........................] - ETA: 5s - loss: 0.1308 - tp: 46196.0000 - fp: 2622.0000 - tn: 45526.0000 - fn: 1912.0000 - accuracy: 0.9529 - precision: 0.9463 - recall: 0.9603 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 5s - loss: 0.1308 - tp: 49121.0000 - fp: 2790.0000 - tn: 48453.0000 - fn: 2036.0000 - accuracy: 0.9529 - precision: 0.9463 - recall: 0.9602 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 5s - loss: 0.1311 - tp: 52000.0000 - fp: 2969.0000 - tn: 51404.0000 - fn: 2171.0000 - accuracy: 0.9526 - precision: 0.9460 - recall: 0.9599 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1311 - tp: 55007.0000 - fp: 3148.0000 - tn: 54237.0000 - fn: 2296.0000 - accuracy: 0.9525 - precision: 0.9459 - recall: 0.9599 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1309 - tp: 57990.0000 - fp: 3301.0000 - tn: 57130.0000 - fn: 2411.0000 - accuracy: 0.9527 - precision: 0.9461 - recall: 0.9601 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1313 - tp: 60971.0000 - fp: 3482.0000 - tn: 59996.0000 - fn: 2527.0000 - accuracy: 0.9527 - precision: 0.9460 - recall: 0.9602 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.1310 - tp: 63934.0000 - fp: 3658.0000 - tn: 62893.0000 - fn: 2635.0000 - accuracy: 0.9527 - precision: 0.9459 - recall: 0.9604 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1311 - tp: 66866.0000 - fp: 3844.0000 - tn: 65816.0000 - fn: 2738.0000 - accuracy: 0.9527 - precision: 0.9456 - recall: 0.9607 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1310 - tp: 69828.0000 - fp: 4008.0000 - tn: 68723.0000 - fn: 2849.0000 - accuracy: 0.9528 - precision: 0.9457 - recall: 0.9608 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1310 - tp: 72783.0000 - fp: 4180.0000 - tn: 71619.0000 - fn: 2970.0000 - accuracy: 0.9528 - precision: 0.9457 - recall: 0.9608 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.1310 - tp: 75767.0000 - fp: 4356.0000 - tn: 74481.0000 - fn: 3092.0000 - accuracy: 0.9528 - precision: 0.9456 - recall: 0.9608 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1310 - tp: 78723.0000 - fp: 4530.0000 - tn: 77381.0000 - fn: 3206.0000 - accuracy: 0.9528 - precision: 0.9456 - recall: 0.9609 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.1307 - tp: 81642.0000 - fp: 4681.0000 - tn: 80342.0000 - fn: 3319.0000 - accuracy: 0.9529 - precision: 0.9458 - recall: 0.9609 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 4s - loss: 0.1308 - tp: 84598.0000 - fp: 4841.0000 - tn: 83251.0000 - fn: 3438.0000 - accuracy: 0.9530 - precision: 0.9459 - recall: 0.9609 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 4s - loss: 0.1310 - tp: 87528.0000 - fp: 5047.0000 - tn: 86151.0000 - fn: 3546.0000 - accuracy: 0.9529 - precision: 0.9455 - recall: 0.9611 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 4s - loss: 0.1309 - tp: 90505.0000 - fp: 5231.0000 - tn: 89016.0000 - fn: 3664.0000 - accuracy: 0.9528 - precision: 0.9454 - recall: 0.9611 - auc: 0.9907 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 4s - loss: 0.1309 - tp: 93482.0000 - fp: 5390.0000 - tn: 91914.0000 - fn: 3774.0000 - accuracy: 0.9529 - precision: 0.9455 - recall: 0.9612 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 4s - loss: 0.1310 - tp: 96451.0000 - fp: 5558.0000 - tn: 94816.0000 - fn: 3879.0000 - accuracy: 0.9530 - precision: 0.9455 - recall: 0.9613 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1311 - tp: 99497.0000 - fp: 5719.0000 - tn: 97659.0000 - fn: 3973.0000 - accuracy: 0.9531 - precision: 0.9456 - recall: 0.9616 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1310 - tp: 102476.0000 - fp: 5891.0000 - tn: 100552.0000 - fn: 4073.0000 - accuracy: 0.9532 - precision: 0.9456 - recall: 0.9618 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1309 - tp: 105510.0000 - fp: 6035.0000 - tn: 103407.0000 - fn: 4184.0000 - accuracy: 0.9534 - precision: 0.9459 - recall: 0.9619 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1310 - tp: 108473.0000 - fp: 6191.0000 - tn: 106322.0000 - fn: 4294.0000 - accuracy: 0.9535 - precision: 0.9460 - recall: 0.9619 - auc: 0.9908 - prc: 0.9905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1309 - tp: 111474.0000 - fp: 6351.0000 - tn: 109184.0000 - fn: 4415.0000 - accuracy: 0.9535 - precision: 0.9461 - recall: 0.9619 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1308 - tp: 114484.0000 - fp: 6508.0000 - tn: 112046.0000 - fn: 4530.0000 - accuracy: 0.9535 - precision: 0.9462 - recall: 0.9619 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1309 - tp: 117513.0000 - fp: 6698.0000 - tn: 114866.0000 - fn: 4635.0000 - accuracy: 0.9535 - precision: 0.9461 - recall: 0.9621 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1309 - tp: 120402.0000 - fp: 6887.0000 - tn: 117824.0000 - fn: 4743.0000 - accuracy: 0.9535 - precision: 0.9459 - recall: 0.9621 - auc: 0.9908 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1307 - tp: 123378.0000 - fp: 7043.0000 - tn: 120731.0000 - fn: 4848.0000 - accuracy: 0.9536 - precision: 0.9460 - recall: 0.9622 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1306 - tp: 126359.0000 - fp: 7202.0000 - tn: 123634.0000 - fn: 4949.0000 - accuracy: 0.9536 - precision: 0.9461 - recall: 0.9623 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1305 - tp: 129270.0000 - fp: 7365.0000 - tn: 126605.0000 - fn: 5048.0000 - accuracy: 0.9537 - precision: 0.9461 - recall: 0.9624 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 3s - loss: 0.1304 - tp: 132225.0000 - fp: 7548.0000 - tn: 129499.0000 - fn: 5160.0000 - accuracy: 0.9537 - precision: 0.9460 - recall: 0.9624 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.1304 - tp: 135206.0000 - fp: 7713.0000 - tn: 132378.0000 - fn: 5279.0000 - accuracy: 0.9537 - precision: 0.9460 - recall: 0.9624 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/278 [==============>...............] - ETA: 3s - loss: 0.1305 - tp: 138136.0000 - fp: 7917.0000 - tn: 135279.0000 - fn: 5388.0000 - accuracy: 0.9536 - precision: 0.9458 - recall: 0.9625 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "143/278 [==============>...............] - ETA: 3s - loss: 0.1305 - tp: 141090.0000 - fp: 8089.0000 - tn: 138185.0000 - fn: 5500.0000 - accuracy: 0.9536 - precision: 0.9458 - recall: 0.9625 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.1303 - tp: 144063.0000 - fp: 8244.0000 - tn: 141092.0000 - fn: 5609.0000 - accuracy: 0.9537 - precision: 0.9459 - recall: 0.9625 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.1303 - tp: 147018.0000 - fp: 8408.0000 - tn: 144004.0000 - fn: 5722.0000 - accuracy: 0.9537 - precision: 0.9459 - recall: 0.9625 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1303 - tp: 150021.0000 - fp: 8586.0000 - tn: 146855.0000 - fn: 5834.0000 - accuracy: 0.9537 - precision: 0.9459 - recall: 0.9626 - auc: 0.9909 - prc: 0.9906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1302 - tp: 152989.0000 - fp: 8735.0000 - tn: 149765.0000 - fn: 5951.0000 - accuracy: 0.9537 - precision: 0.9460 - recall: 0.9626 - auc: 0.9909 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1302 - tp: 155992.0000 - fp: 8910.0000 - tn: 152632.0000 - fn: 6050.0000 - accuracy: 0.9538 - precision: 0.9460 - recall: 0.9627 - auc: 0.9909 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1301 - tp: 158974.0000 - fp: 9082.0000 - tn: 155523.0000 - fn: 6149.0000 - accuracy: 0.9538 - precision: 0.9460 - recall: 0.9628 - auc: 0.9909 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.1301 - tp: 160945.0000 - fp: 9184.0000 - tn: 157473.0000 - fn: 6222.0000 - accuracy: 0.9538 - precision: 0.9460 - recall: 0.9628 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.1300 - tp: 163966.0000 - fp: 9350.0000 - tn: 160330.0000 - fn: 6322.0000 - accuracy: 0.9539 - precision: 0.9461 - recall: 0.9629 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.1298 - tp: 166894.0000 - fp: 9511.0000 - tn: 163282.0000 - fn: 6425.0000 - accuracy: 0.9540 - precision: 0.9461 - recall: 0.9629 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.1298 - tp: 169804.0000 - fp: 9682.0000 - tn: 166251.0000 - fn: 6519.0000 - accuracy: 0.9540 - precision: 0.9461 - recall: 0.9630 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.1297 - tp: 172749.0000 - fp: 9858.0000 - tn: 169177.0000 - fn: 6616.0000 - accuracy: 0.9540 - precision: 0.9460 - recall: 0.9631 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.1296 - tp: 175687.0000 - fp: 10036.0000 - tn: 172102.0000 - fn: 6719.0000 - accuracy: 0.9540 - precision: 0.9460 - recall: 0.9632 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.1297 - tp: 178703.0000 - fp: 10208.0000 - tn: 174936.0000 - fn: 6841.0000 - accuracy: 0.9540 - precision: 0.9460 - recall: 0.9631 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/278 [==================>...........] - ETA: 2s - loss: 0.1297 - tp: 181688.0000 - fp: 10396.0000 - tn: 177799.0000 - fn: 6949.0000 - accuracy: 0.9540 - precision: 0.9459 - recall: 0.9632 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 2s - loss: 0.1297 - tp: 184648.0000 - fp: 10568.0000 - tn: 180700.0000 - fn: 7060.0000 - accuracy: 0.9540 - precision: 0.9459 - recall: 0.9632 - auc: 0.9910 - prc: 0.9907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/278 [===================>..........] - ETA: 1s - loss: 0.1294 - tp: 187636.0000 - fp: 10717.0000 - tn: 183602.0000 - fn: 7165.0000 - accuracy: 0.9540 - precision: 0.9460 - recall: 0.9632 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.1294 - tp: 190638.0000 - fp: 10875.0000 - tn: 186479.0000 - fn: 7272.0000 - accuracy: 0.9541 - precision: 0.9460 - recall: 0.9633 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1294 - tp: 193619.0000 - fp: 11046.0000 - tn: 189367.0000 - fn: 7376.0000 - accuracy: 0.9541 - precision: 0.9460 - recall: 0.9633 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1293 - tp: 196612.0000 - fp: 11230.0000 - tn: 192231.0000 - fn: 7479.0000 - accuracy: 0.9541 - precision: 0.9460 - recall: 0.9634 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "201/278 [====================>.........] - ETA: 1s - loss: 0.1293 - tp: 198627.0000 - fp: 11332.0000 - tn: 194154.0000 - fn: 7535.0000 - accuracy: 0.9542 - precision: 0.9460 - recall: 0.9635 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "204/278 [=====================>........] - ETA: 1s - loss: 0.1292 - tp: 201611.0000 - fp: 11511.0000 - tn: 197034.0000 - fn: 7636.0000 - accuracy: 0.9542 - precision: 0.9460 - recall: 0.9635 - auc: 0.9910 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "207/278 [=====================>........] - ETA: 1s - loss: 0.1292 - tp: 204618.0000 - fp: 11668.0000 - tn: 199919.0000 - fn: 7731.0000 - accuracy: 0.9542 - precision: 0.9461 - recall: 0.9636 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "210/278 [=====================>........] - ETA: 1s - loss: 0.1292 - tp: 207654.0000 - fp: 11831.0000 - tn: 202760.0000 - fn: 7835.0000 - accuracy: 0.9543 - precision: 0.9461 - recall: 0.9636 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.1291 - tp: 210667.0000 - fp: 11990.0000 - tn: 205632.0000 - fn: 7935.0000 - accuracy: 0.9543 - precision: 0.9462 - recall: 0.9637 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "216/278 [======================>.......] - ETA: 1s - loss: 0.1291 - tp: 213637.0000 - fp: 12163.0000 - tn: 208539.0000 - fn: 8029.0000 - accuracy: 0.9544 - precision: 0.9461 - recall: 0.9638 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.1290 - tp: 216653.0000 - fp: 12339.0000 - tn: 211399.0000 - fn: 8121.0000 - accuracy: 0.9544 - precision: 0.9461 - recall: 0.9639 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.1289 - tp: 219626.0000 - fp: 12504.0000 - tn: 214302.0000 - fn: 8224.0000 - accuracy: 0.9544 - precision: 0.9461 - recall: 0.9639 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.1289 - tp: 222611.0000 - fp: 12680.0000 - tn: 217187.0000 - fn: 8322.0000 - accuracy: 0.9544 - precision: 0.9461 - recall: 0.9640 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.1289 - tp: 225531.0000 - fp: 12871.0000 - tn: 220120.0000 - fn: 8422.0000 - accuracy: 0.9544 - precision: 0.9460 - recall: 0.9640 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "231/278 [=======================>......] - ETA: 1s - loss: 0.1289 - tp: 228542.0000 - fp: 13039.0000 - tn: 222974.0000 - fn: 8533.0000 - accuracy: 0.9544 - precision: 0.9460 - recall: 0.9640 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.1289 - tp: 231496.0000 - fp: 13233.0000 - tn: 225861.0000 - fn: 8642.0000 - accuracy: 0.9544 - precision: 0.9459 - recall: 0.9640 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.1288 - tp: 234476.0000 - fp: 13399.0000 - tn: 228759.0000 - fn: 8742.0000 - accuracy: 0.9544 - precision: 0.9459 - recall: 0.9641 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.1287 - tp: 237418.0000 - fp: 13568.0000 - tn: 231706.0000 - fn: 8828.0000 - accuracy: 0.9544 - precision: 0.9459 - recall: 0.9641 - auc: 0.9911 - prc: 0.9908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.1286 - tp: 240374.0000 - fp: 13731.0000 - tn: 234626.0000 - fn: 8933.0000 - accuracy: 0.9545 - precision: 0.9460 - recall: 0.9642 - auc: 0.9911 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.1285 - tp: 243359.0000 - fp: 13898.0000 - tn: 237509.0000 - fn: 9042.0000 - accuracy: 0.9545 - precision: 0.9460 - recall: 0.9642 - auc: 0.9911 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.1285 - tp: 246359.0000 - fp: 14080.0000 - tn: 240356.0000 - fn: 9157.0000 - accuracy: 0.9544 - precision: 0.9459 - recall: 0.9642 - auc: 0.9911 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1285 - tp: 249316.0000 - fp: 14263.0000 - tn: 243270.0000 - fn: 9247.0000 - accuracy: 0.9544 - precision: 0.9459 - recall: 0.9642 - auc: 0.9911 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1283 - tp: 252285.0000 - fp: 14412.0000 - tn: 246195.0000 - fn: 9348.0000 - accuracy: 0.9545 - precision: 0.9460 - recall: 0.9643 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1284 - tp: 255226.0000 - fp: 14623.0000 - tn: 249088.0000 - fn: 9447.0000 - accuracy: 0.9544 - precision: 0.9458 - recall: 0.9643 - auc: 0.9911 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1283 - tp: 258228.0000 - fp: 14792.0000 - tn: 251973.0000 - fn: 9535.0000 - accuracy: 0.9545 - precision: 0.9458 - recall: 0.9644 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1281 - tp: 261243.0000 - fp: 14956.0000 - tn: 254847.0000 - fn: 9626.0000 - accuracy: 0.9545 - precision: 0.9459 - recall: 0.9645 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1281 - tp: 264188.0000 - fp: 15132.0000 - tn: 257772.0000 - fn: 9724.0000 - accuracy: 0.9545 - precision: 0.9458 - recall: 0.9645 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1281 - tp: 267187.0000 - fp: 15314.0000 - tn: 260641.0000 - fn: 9818.0000 - accuracy: 0.9546 - precision: 0.9458 - recall: 0.9646 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1280 - tp: 270171.0000 - fp: 15511.0000 - tn: 263516.0000 - fn: 9906.0000 - accuracy: 0.9545 - precision: 0.9457 - recall: 0.9646 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1279 - tp: 273175.0000 - fp: 15683.0000 - tn: 266385.0000 - fn: 10005.0000 - accuracy: 0.9546 - precision: 0.9457 - recall: 0.9647 - auc: 0.9912 - prc: 0.9909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.1279 - tp: 275144.0000 - fp: 15791.0000 - tn: 268338.0000 - fn: 10071.0000 - accuracy: 0.9546 - precision: 0.9457 - recall: 0.9647 - auc: 0.9912 - prc: 0.9909 - val_loss: 0.0474 - val_tp: 65.0000 - val_fp: 720.0000 - val_tn: 44780.0000 - val_fn: 4.0000 - val_accuracy: 0.9841 - val_precision: 0.0828 - val_recall: 0.9420 - val_auc: 0.9955 - val_prc: 0.7776\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1251 - tp: 1014.0000 - fp: 48.0000 - tn: 957.0000 - fn: 29.0000 - accuracy: 0.9624 - precision: 0.9548 - recall: 0.9722 - auc: 0.9917 - prc: 0.9912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1245 - tp: 4981.0000 - fp: 280.0000 - tn: 4803.0000 - fn: 176.0000 - accuracy: 0.9555 - precision: 0.9468 - recall: 0.9659 - auc: 0.9915 - prc: 0.9913"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1241 - tp: 7939.0000 - fp: 452.0000 - tn: 7711.0000 - fn: 282.0000 - accuracy: 0.9552 - precision: 0.9461 - recall: 0.9657 - auc: 0.9914 - prc: 0.9913"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1231 - tp: 10888.0000 - fp: 630.0000 - tn: 10644.0000 - fn: 366.0000 - accuracy: 0.9558 - precision: 0.9453 - recall: 0.9675 - auc: 0.9917 - prc: 0.9914"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1227 - tp: 13827.0000 - fp: 797.0000 - tn: 13583.0000 - fn: 465.0000 - accuracy: 0.9560 - precision: 0.9455 - recall: 0.9675 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1222 - tp: 16788.0000 - fp: 958.0000 - tn: 16516.0000 - fn: 554.0000 - accuracy: 0.9566 - precision: 0.9460 - recall: 0.9681 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1219 - tp: 19859.0000 - fp: 1104.0000 - tn: 19344.0000 - fn: 653.0000 - accuracy: 0.9571 - precision: 0.9473 - recall: 0.9682 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1219 - tp: 22807.0000 - fp: 1286.0000 - tn: 22264.0000 - fn: 747.0000 - accuracy: 0.9568 - precision: 0.9466 - recall: 0.9683 - auc: 0.9919 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.1221 - tp: 25793.0000 - fp: 1464.0000 - tn: 25142.0000 - fn: 849.0000 - accuracy: 0.9566 - precision: 0.9463 - recall: 0.9681 - auc: 0.9919 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.1216 - tp: 28802.0000 - fp: 1635.0000 - tn: 28012.0000 - fn: 943.0000 - accuracy: 0.9566 - precision: 0.9463 - recall: 0.9683 - auc: 0.9920 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.1212 - tp: 31857.0000 - fp: 1793.0000 - tn: 30838.0000 - fn: 1048.0000 - accuracy: 0.9566 - precision: 0.9467 - recall: 0.9682 - auc: 0.9920 - prc: 0.9919"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.1212 - tp: 33821.0000 - fp: 1890.0000 - tn: 32806.0000 - fn: 1115.0000 - accuracy: 0.9568 - precision: 0.9471 - recall: 0.9681 - auc: 0.9920 - prc: 0.9919"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.1214 - tp: 36783.0000 - fp: 2070.0000 - tn: 35719.0000 - fn: 1204.0000 - accuracy: 0.9568 - precision: 0.9467 - recall: 0.9683 - auc: 0.9920 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/278 [===>..........................] - ETA: 5s - loss: 0.1214 - tp: 38741.0000 - fp: 2183.0000 - tn: 37681.0000 - fn: 1267.0000 - accuracy: 0.9568 - precision: 0.9467 - recall: 0.9683 - auc: 0.9920 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 5s - loss: 0.1213 - tp: 40752.0000 - fp: 2281.0000 - tn: 39603.0000 - fn: 1332.0000 - accuracy: 0.9570 - precision: 0.9470 - recall: 0.9683 - auc: 0.9920 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/278 [===>..........................] - ETA: 5s - loss: 0.1215 - tp: 43713.0000 - fp: 2484.0000 - tn: 42501.0000 - fn: 1414.0000 - accuracy: 0.9567 - precision: 0.9462 - recall: 0.9687 - auc: 0.9919 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/278 [====>.........................] - ETA: 5s - loss: 0.1217 - tp: 46692.0000 - fp: 2664.0000 - tn: 45390.0000 - fn: 1510.0000 - accuracy: 0.9566 - precision: 0.9460 - recall: 0.9687 - auc: 0.9919 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 5s - loss: 0.1219 - tp: 49668.0000 - fp: 2841.0000 - tn: 48286.0000 - fn: 1605.0000 - accuracy: 0.9566 - precision: 0.9459 - recall: 0.9687 - auc: 0.9919 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 5s - loss: 0.1220 - tp: 52653.0000 - fp: 3031.0000 - tn: 51162.0000 - fn: 1698.0000 - accuracy: 0.9564 - precision: 0.9456 - recall: 0.9688 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1222 - tp: 55678.0000 - fp: 3210.0000 - tn: 54008.0000 - fn: 1792.0000 - accuracy: 0.9564 - precision: 0.9455 - recall: 0.9688 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1221 - tp: 58678.0000 - fp: 3381.0000 - tn: 56878.0000 - fn: 1895.0000 - accuracy: 0.9563 - precision: 0.9455 - recall: 0.9687 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1224 - tp: 61618.0000 - fp: 3562.0000 - tn: 59804.0000 - fn: 1992.0000 - accuracy: 0.9563 - precision: 0.9454 - recall: 0.9687 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.1226 - tp: 64632.0000 - fp: 3731.0000 - tn: 62677.0000 - fn: 2080.0000 - accuracy: 0.9563 - precision: 0.9454 - recall: 0.9688 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1225 - tp: 67618.0000 - fp: 3899.0000 - tn: 65572.0000 - fn: 2175.0000 - accuracy: 0.9564 - precision: 0.9455 - recall: 0.9688 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1227 - tp: 70522.0000 - fp: 4075.0000 - tn: 68544.0000 - fn: 2267.0000 - accuracy: 0.9564 - precision: 0.9454 - recall: 0.9689 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/278 [======>.......................] - ETA: 4s - loss: 0.1227 - tp: 72503.0000 - fp: 4185.0000 - tn: 70485.0000 - fn: 2331.0000 - accuracy: 0.9564 - precision: 0.9454 - recall: 0.9689 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 76/278 [=======>......................] - ETA: 4s - loss: 0.1228 - tp: 75551.0000 - fp: 4371.0000 - tn: 73303.0000 - fn: 2423.0000 - accuracy: 0.9564 - precision: 0.9453 - recall: 0.9689 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 0.1227 - tp: 78529.0000 - fp: 4540.0000 - tn: 76191.0000 - fn: 2532.0000 - accuracy: 0.9563 - precision: 0.9453 - recall: 0.9688 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/278 [=======>......................] - ETA: 4s - loss: 0.1227 - tp: 80539.0000 - fp: 4657.0000 - tn: 78097.0000 - fn: 2595.0000 - accuracy: 0.9563 - precision: 0.9453 - recall: 0.9688 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/278 [========>.....................] - ETA: 4s - loss: 0.1227 - tp: 83502.0000 - fp: 4825.0000 - tn: 81010.0000 - fn: 2695.0000 - accuracy: 0.9563 - precision: 0.9454 - recall: 0.9687 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 87/278 [========>.....................] - ETA: 4s - loss: 0.1225 - tp: 86417.0000 - fp: 4988.0000 - tn: 83984.0000 - fn: 2787.0000 - accuracy: 0.9564 - precision: 0.9454 - recall: 0.9688 - auc: 0.9918 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 90/278 [========>.....................] - ETA: 4s - loss: 0.1227 - tp: 89373.0000 - fp: 5179.0000 - tn: 86897.0000 - fn: 2871.0000 - accuracy: 0.9563 - precision: 0.9452 - recall: 0.9689 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 93/278 [=========>....................] - ETA: 4s - loss: 0.1228 - tp: 92330.0000 - fp: 5367.0000 - tn: 89810.0000 - fn: 2957.0000 - accuracy: 0.9563 - precision: 0.9451 - recall: 0.9690 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/278 [=========>....................] - ETA: 4s - loss: 0.1227 - tp: 95283.0000 - fp: 5556.0000 - tn: 92720.0000 - fn: 3049.0000 - accuracy: 0.9562 - precision: 0.9449 - recall: 0.9690 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 99/278 [=========>....................] - ETA: 4s - loss: 0.1225 - tp: 98258.0000 - fp: 5725.0000 - tn: 95624.0000 - fn: 3145.0000 - accuracy: 0.9563 - precision: 0.9449 - recall: 0.9690 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "102/278 [==========>...................] - ETA: 3s - loss: 0.1225 - tp: 101236.0000 - fp: 5882.0000 - tn: 98533.0000 - fn: 3245.0000 - accuracy: 0.9563 - precision: 0.9451 - recall: 0.9689 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "105/278 [==========>...................] - ETA: 3s - loss: 0.1223 - tp: 104243.0000 - fp: 6035.0000 - tn: 101418.0000 - fn: 3344.0000 - accuracy: 0.9564 - precision: 0.9453 - recall: 0.9689 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1223 - tp: 106242.0000 - fp: 6152.0000 - tn: 103345.0000 - fn: 3397.0000 - accuracy: 0.9564 - precision: 0.9453 - recall: 0.9690 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1223 - tp: 109202.0000 - fp: 6327.0000 - tn: 106265.0000 - fn: 3486.0000 - accuracy: 0.9564 - precision: 0.9452 - recall: 0.9691 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1223 - tp: 112183.0000 - fp: 6496.0000 - tn: 109169.0000 - fn: 3576.0000 - accuracy: 0.9565 - precision: 0.9453 - recall: 0.9691 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1221 - tp: 115149.0000 - fp: 6676.0000 - tn: 112089.0000 - fn: 3654.0000 - accuracy: 0.9565 - precision: 0.9452 - recall: 0.9692 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1222 - tp: 118078.0000 - fp: 6884.0000 - tn: 115014.0000 - fn: 3736.0000 - accuracy: 0.9564 - precision: 0.9449 - recall: 0.9693 - auc: 0.9919 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1221 - tp: 121033.0000 - fp: 7051.0000 - tn: 117935.0000 - fn: 3837.0000 - accuracy: 0.9564 - precision: 0.9450 - recall: 0.9693 - auc: 0.9919 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1221 - tp: 124016.0000 - fp: 7220.0000 - tn: 120832.0000 - fn: 3932.0000 - accuracy: 0.9564 - precision: 0.9450 - recall: 0.9693 - auc: 0.9919 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1221 - tp: 127066.0000 - fp: 7402.0000 - tn: 123655.0000 - fn: 4021.0000 - accuracy: 0.9564 - precision: 0.9450 - recall: 0.9693 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1222 - tp: 130033.0000 - fp: 7595.0000 - tn: 126537.0000 - fn: 4123.0000 - accuracy: 0.9563 - precision: 0.9448 - recall: 0.9693 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 3s - loss: 0.1222 - tp: 132965.0000 - fp: 7765.0000 - tn: 129484.0000 - fn: 4218.0000 - accuracy: 0.9563 - precision: 0.9448 - recall: 0.9693 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.1221 - tp: 136031.0000 - fp: 7932.0000 - tn: 132309.0000 - fn: 4304.0000 - accuracy: 0.9564 - precision: 0.9449 - recall: 0.9693 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/278 [==============>...............] - ETA: 3s - loss: 0.1221 - tp: 139020.0000 - fp: 8098.0000 - tn: 135210.0000 - fn: 4392.0000 - accuracy: 0.9564 - precision: 0.9450 - recall: 0.9694 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.1221 - tp: 141069.0000 - fp: 8206.0000 - tn: 137090.0000 - fn: 4451.0000 - accuracy: 0.9565 - precision: 0.9450 - recall: 0.9694 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 3s - loss: 0.1220 - tp: 144053.0000 - fp: 8361.0000 - tn: 140007.0000 - fn: 4539.0000 - accuracy: 0.9566 - precision: 0.9451 - recall: 0.9695 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1220 - tp: 147031.0000 - fp: 8537.0000 - tn: 142903.0000 - fn: 4633.0000 - accuracy: 0.9565 - precision: 0.9451 - recall: 0.9695 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1220 - tp: 150016.0000 - fp: 8719.0000 - tn: 145792.0000 - fn: 4721.0000 - accuracy: 0.9565 - precision: 0.9451 - recall: 0.9695 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1220 - tp: 153050.0000 - fp: 8897.0000 - tn: 148631.0000 - fn: 4814.0000 - accuracy: 0.9565 - precision: 0.9451 - recall: 0.9695 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.1220 - tp: 156080.0000 - fp: 9084.0000 - tn: 151478.0000 - fn: 4894.0000 - accuracy: 0.9565 - precision: 0.9450 - recall: 0.9696 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.1220 - tp: 159002.0000 - fp: 9267.0000 - tn: 154437.0000 - fn: 4974.0000 - accuracy: 0.9565 - precision: 0.9449 - recall: 0.9697 - auc: 0.9919 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.1220 - tp: 162027.0000 - fp: 9452.0000 - tn: 157287.0000 - fn: 5058.0000 - accuracy: 0.9565 - precision: 0.9449 - recall: 0.9697 - auc: 0.9919 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.1220 - tp: 164950.0000 - fp: 9646.0000 - tn: 160230.0000 - fn: 5142.0000 - accuracy: 0.9565 - precision: 0.9448 - recall: 0.9698 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.1219 - tp: 167997.0000 - fp: 9836.0000 - tn: 163043.0000 - fn: 5236.0000 - accuracy: 0.9565 - precision: 0.9447 - recall: 0.9698 - auc: 0.9918 - prc: 0.9915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.1217 - tp: 170999.0000 - fp: 9999.0000 - tn: 165944.0000 - fn: 5314.0000 - accuracy: 0.9565 - precision: 0.9448 - recall: 0.9699 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.1217 - tp: 173948.0000 - fp: 10175.0000 - tn: 168888.0000 - fn: 5389.0000 - accuracy: 0.9566 - precision: 0.9447 - recall: 0.9700 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.1216 - tp: 176942.0000 - fp: 10341.0000 - tn: 171780.0000 - fn: 5481.0000 - accuracy: 0.9566 - precision: 0.9448 - recall: 0.9700 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.1215 - tp: 179900.0000 - fp: 10515.0000 - tn: 174705.0000 - fn: 5568.0000 - accuracy: 0.9566 - precision: 0.9448 - recall: 0.9700 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/278 [==================>...........] - ETA: 2s - loss: 0.1214 - tp: 182898.0000 - fp: 10692.0000 - tn: 177588.0000 - fn: 5654.0000 - accuracy: 0.9566 - precision: 0.9448 - recall: 0.9700 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 2s - loss: 0.1214 - tp: 185891.0000 - fp: 10878.0000 - tn: 180467.0000 - fn: 5740.0000 - accuracy: 0.9566 - precision: 0.9447 - recall: 0.9700 - auc: 0.9919 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/278 [===================>..........] - ETA: 1s - loss: 0.1213 - tp: 188832.0000 - fp: 11041.0000 - tn: 183421.0000 - fn: 5826.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9701 - auc: 0.9920 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.1212 - tp: 191822.0000 - fp: 11209.0000 - tn: 186326.0000 - fn: 5907.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9701 - auc: 0.9920 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1212 - tp: 194894.0000 - fp: 11390.0000 - tn: 189126.0000 - fn: 5998.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9701 - auc: 0.9920 - prc: 0.9916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1212 - tp: 197857.0000 - fp: 11569.0000 - tn: 192044.0000 - fn: 6082.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9702 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.1211 - tp: 200840.0000 - fp: 11727.0000 - tn: 194950.0000 - fn: 6179.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9702 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.1211 - tp: 203922.0000 - fp: 11894.0000 - tn: 197754.0000 - fn: 6270.0000 - accuracy: 0.9567 - precision: 0.9449 - recall: 0.9702 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.1211 - tp: 206949.0000 - fp: 12076.0000 - tn: 200589.0000 - fn: 6370.0000 - accuracy: 0.9567 - precision: 0.9449 - recall: 0.9701 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.1211 - tp: 209959.0000 - fp: 12267.0000 - tn: 203452.0000 - fn: 6450.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9702 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "214/278 [======================>.......] - ETA: 1s - loss: 0.1211 - tp: 212928.0000 - fp: 12453.0000 - tn: 206364.0000 - fn: 6527.0000 - accuracy: 0.9567 - precision: 0.9447 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "217/278 [======================>.......] - ETA: 1s - loss: 0.1210 - tp: 216005.0000 - fp: 12610.0000 - tn: 209200.0000 - fn: 6601.0000 - accuracy: 0.9568 - precision: 0.9448 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "220/278 [======================>.......] - ETA: 1s - loss: 0.1210 - tp: 219017.0000 - fp: 12793.0000 - tn: 212057.0000 - fn: 6693.0000 - accuracy: 0.9568 - precision: 0.9448 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "223/278 [=======================>......] - ETA: 1s - loss: 0.1209 - tp: 222053.0000 - fp: 12960.0000 - tn: 214918.0000 - fn: 6773.0000 - accuracy: 0.9568 - precision: 0.9449 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.1209 - tp: 224078.0000 - fp: 13073.0000 - tn: 216816.0000 - fn: 6833.0000 - accuracy: 0.9568 - precision: 0.9449 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.1210 - tp: 227073.0000 - fp: 13267.0000 - tn: 219672.0000 - fn: 6932.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "231/278 [=======================>......] - ETA: 1s - loss: 0.1210 - tp: 230064.0000 - fp: 13451.0000 - tn: 222549.0000 - fn: 7024.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.1209 - tp: 233123.0000 - fp: 13622.0000 - tn: 225363.0000 - fn: 7124.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "236/278 [========================>.....] - ETA: 0s - loss: 0.1209 - tp: 235042.0000 - fp: 13750.0000 - tn: 227351.0000 - fn: 7185.0000 - accuracy: 0.9567 - precision: 0.9447 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "239/278 [========================>.....] - ETA: 0s - loss: 0.1209 - tp: 238021.0000 - fp: 13923.0000 - tn: 230254.0000 - fn: 7274.0000 - accuracy: 0.9567 - precision: 0.9447 - recall: 0.9703 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "242/278 [=========================>....] - ETA: 0s - loss: 0.1209 - tp: 241008.0000 - fp: 14115.0000 - tn: 233130.0000 - fn: 7363.0000 - accuracy: 0.9567 - precision: 0.9447 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "245/278 [=========================>....] - ETA: 0s - loss: 0.1208 - tp: 244063.0000 - fp: 14276.0000 - tn: 235966.0000 - fn: 7455.0000 - accuracy: 0.9567 - precision: 0.9447 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "248/278 [=========================>....] - ETA: 0s - loss: 0.1207 - tp: 247017.0000 - fp: 14427.0000 - tn: 238920.0000 - fn: 7540.0000 - accuracy: 0.9567 - precision: 0.9448 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "251/278 [==========================>...] - ETA: 0s - loss: 0.1206 - tp: 249950.0000 - fp: 14593.0000 - tn: 241878.0000 - fn: 7627.0000 - accuracy: 0.9568 - precision: 0.9448 - recall: 0.9704 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "254/278 [==========================>...] - ETA: 0s - loss: 0.1205 - tp: 252940.0000 - fp: 14764.0000 - tn: 244789.0000 - fn: 7699.0000 - accuracy: 0.9568 - precision: 0.9448 - recall: 0.9705 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "257/278 [==========================>...] - ETA: 0s - loss: 0.1205 - tp: 255887.0000 - fp: 14937.0000 - tn: 247728.0000 - fn: 7784.0000 - accuracy: 0.9568 - precision: 0.9448 - recall: 0.9705 - auc: 0.9920 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "259/278 [==========================>...] - ETA: 0s - loss: 0.1204 - tp: 257866.0000 - fp: 15038.0000 - tn: 249698.0000 - fn: 7830.0000 - accuracy: 0.9569 - precision: 0.9449 - recall: 0.9705 - auc: 0.9921 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "262/278 [===========================>..] - ETA: 0s - loss: 0.1204 - tp: 260863.0000 - fp: 15205.0000 - tn: 252590.0000 - fn: 7918.0000 - accuracy: 0.9569 - precision: 0.9449 - recall: 0.9705 - auc: 0.9921 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "265/278 [===========================>..] - ETA: 0s - loss: 0.1203 - tp: 263869.0000 - fp: 15364.0000 - tn: 255477.0000 - fn: 8010.0000 - accuracy: 0.9569 - precision: 0.9450 - recall: 0.9705 - auc: 0.9921 - prc: 0.9917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "268/278 [===========================>..] - ETA: 0s - loss: 0.1202 - tp: 266873.0000 - fp: 15526.0000 - tn: 258374.0000 - fn: 8091.0000 - accuracy: 0.9570 - precision: 0.9450 - recall: 0.9706 - auc: 0.9921 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "271/278 [============================>.] - ETA: 0s - loss: 0.1202 - tp: 269894.0000 - fp: 15708.0000 - tn: 261230.0000 - fn: 8176.0000 - accuracy: 0.9570 - precision: 0.9450 - recall: 0.9706 - auc: 0.9921 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "274/278 [============================>.] - ETA: 0s - loss: 0.1201 - tp: 272924.0000 - fp: 15889.0000 - tn: 264078.0000 - fn: 8261.0000 - accuracy: 0.9570 - precision: 0.9450 - recall: 0.9706 - auc: 0.9921 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "277/278 [============================>.] - ETA: 0s - loss: 0.1200 - tp: 275950.0000 - fp: 16066.0000 - tn: 266945.0000 - fn: 8335.0000 - accuracy: 0.9570 - precision: 0.9450 - recall: 0.9707 - auc: 0.9921 - prc: 0.9918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.1200 - tp: 276934.0000 - fp: 16125.0000 - tn: 267921.0000 - fn: 8364.0000 - accuracy: 0.9570 - precision: 0.9450 - recall: 0.9707 - auc: 0.9921 - prc: 0.9918 - val_loss: 0.0443 - val_tp: 65.0000 - val_fp: 716.0000 - val_tn: 44784.0000 - val_fn: 4.0000 - val_accuracy: 0.9842 - val_precision: 0.0832 - val_recall: 0.9420 - val_auc: 0.9948 - val_prc: 0.7683\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1095 - tp: 995.0000 - fp: 44.0000 - tn: 983.0000 - fn: 26.0000 - accuracy: 0.9658 - precision: 0.9577 - recall: 0.9745 - auc: 0.9942 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1164 - tp: 4967.0000 - fp: 291.0000 - tn: 4842.0000 - fn: 140.0000 - accuracy: 0.9579 - precision: 0.9447 - recall: 0.9726 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/278 [..............................] - ETA: 5s - loss: 0.1143 - tp: 7042.0000 - fp: 391.0000 - tn: 6706.0000 - fn: 197.0000 - accuracy: 0.9590 - precision: 0.9474 - recall: 0.9728 - auc: 0.9930 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/278 [>.............................] - ETA: 5s - loss: 0.1151 - tp: 10015.0000 - fp: 577.0000 - tn: 9611.0000 - fn: 277.0000 - accuracy: 0.9583 - precision: 0.9455 - recall: 0.9731 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/278 [>.............................] - ETA: 5s - loss: 0.1139 - tp: 13018.0000 - fp: 736.0000 - tn: 12522.0000 - fn: 348.0000 - accuracy: 0.9593 - precision: 0.9465 - recall: 0.9740 - auc: 0.9929 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/278 [>.............................] - ETA: 5s - loss: 0.1137 - tp: 16049.0000 - fp: 910.0000 - tn: 15385.0000 - fn: 424.0000 - accuracy: 0.9593 - precision: 0.9463 - recall: 0.9743 - auc: 0.9929 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/278 [=>............................] - ETA: 5s - loss: 0.1133 - tp: 18981.0000 - fp: 1084.0000 - tn: 18351.0000 - fn: 496.0000 - accuracy: 0.9594 - precision: 0.9460 - recall: 0.9745 - auc: 0.9929 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/278 [=>............................] - ETA: 5s - loss: 0.1131 - tp: 21946.0000 - fp: 1247.0000 - tn: 21286.0000 - fn: 577.0000 - accuracy: 0.9595 - precision: 0.9462 - recall: 0.9744 - auc: 0.9930 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1133 - tp: 24927.0000 - fp: 1435.0000 - tn: 24198.0000 - fn: 640.0000 - accuracy: 0.9595 - precision: 0.9456 - recall: 0.9750 - auc: 0.9929 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1134 - tp: 27926.0000 - fp: 1614.0000 - tn: 27082.0000 - fn: 722.0000 - accuracy: 0.9593 - precision: 0.9454 - recall: 0.9748 - auc: 0.9930 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/278 [==>...........................] - ETA: 5s - loss: 0.1133 - tp: 29944.0000 - fp: 1715.0000 - tn: 29015.0000 - fn: 766.0000 - accuracy: 0.9596 - precision: 0.9458 - recall: 0.9751 - auc: 0.9930 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 33/278 [==>...........................] - ETA: 5s - loss: 0.1132 - tp: 32944.0000 - fp: 1871.0000 - tn: 31914.0000 - fn: 855.0000 - accuracy: 0.9597 - precision: 0.9463 - recall: 0.9747 - auc: 0.9930 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/278 [==>...........................] - ETA: 5s - loss: 0.1133 - tp: 35903.0000 - fp: 2053.0000 - tn: 34840.0000 - fn: 932.0000 - accuracy: 0.9595 - precision: 0.9459 - recall: 0.9747 - auc: 0.9930 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/278 [===>..........................] - ETA: 5s - loss: 0.1134 - tp: 38894.0000 - fp: 2245.0000 - tn: 37718.0000 - fn: 1015.0000 - accuracy: 0.9592 - precision: 0.9454 - recall: 0.9746 - auc: 0.9929 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/278 [===>..........................] - ETA: 5s - loss: 0.1135 - tp: 41849.0000 - fp: 2430.0000 - tn: 40648.0000 - fn: 1089.0000 - accuracy: 0.9591 - precision: 0.9451 - recall: 0.9746 - auc: 0.9929 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/278 [===>..........................] - ETA: 5s - loss: 0.1137 - tp: 44813.0000 - fp: 2610.0000 - tn: 43574.0000 - fn: 1163.0000 - accuracy: 0.9591 - precision: 0.9450 - recall: 0.9747 - auc: 0.9929 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/278 [====>.........................] - ETA: 5s - loss: 0.1138 - tp: 47787.0000 - fp: 2794.0000 - tn: 46481.0000 - fn: 1242.0000 - accuracy: 0.9589 - precision: 0.9448 - recall: 0.9747 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/278 [====>.........................] - ETA: 5s - loss: 0.1138 - tp: 50749.0000 - fp: 2977.0000 - tn: 49395.0000 - fn: 1327.0000 - accuracy: 0.9588 - precision: 0.9446 - recall: 0.9745 - auc: 0.9929 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/278 [====>.........................] - ETA: 5s - loss: 0.1144 - tp: 53721.0000 - fp: 3178.0000 - tn: 52283.0000 - fn: 1410.0000 - accuracy: 0.9585 - precision: 0.9441 - recall: 0.9744 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/278 [=====>........................] - ETA: 4s - loss: 0.1142 - tp: 56738.0000 - fp: 3332.0000 - tn: 55183.0000 - fn: 1483.0000 - accuracy: 0.9588 - precision: 0.9445 - recall: 0.9745 - auc: 0.9928 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/278 [=====>........................] - ETA: 4s - loss: 0.1143 - tp: 59716.0000 - fp: 3514.0000 - tn: 58096.0000 - fn: 1554.0000 - accuracy: 0.9588 - precision: 0.9444 - recall: 0.9746 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/278 [=====>........................] - ETA: 4s - loss: 0.1143 - tp: 62731.0000 - fp: 3698.0000 - tn: 60965.0000 - fn: 1630.0000 - accuracy: 0.9587 - precision: 0.9443 - recall: 0.9747 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 66/278 [======>.......................] - ETA: 4s - loss: 0.1144 - tp: 65744.0000 - fp: 3877.0000 - tn: 63836.0000 - fn: 1711.0000 - accuracy: 0.9587 - precision: 0.9443 - recall: 0.9746 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/278 [======>.......................] - ETA: 4s - loss: 0.1143 - tp: 68722.0000 - fp: 4045.0000 - tn: 66755.0000 - fn: 1790.0000 - accuracy: 0.9587 - precision: 0.9444 - recall: 0.9746 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/278 [======>.......................] - ETA: 4s - loss: 0.1143 - tp: 71753.0000 - fp: 4199.0000 - tn: 69642.0000 - fn: 1862.0000 - accuracy: 0.9589 - precision: 0.9447 - recall: 0.9747 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/278 [=======>......................] - ETA: 4s - loss: 0.1140 - tp: 74751.0000 - fp: 4361.0000 - tn: 72560.0000 - fn: 1928.0000 - accuracy: 0.9591 - precision: 0.9449 - recall: 0.9749 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 78/278 [=======>......................] - ETA: 4s - loss: 0.1143 - tp: 77732.0000 - fp: 4582.0000 - tn: 75433.0000 - fn: 1997.0000 - accuracy: 0.9588 - precision: 0.9443 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1143 - tp: 79754.0000 - fp: 4719.0000 - tn: 77317.0000 - fn: 2050.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9749 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.1144 - tp: 82742.0000 - fp: 4919.0000 - tn: 80195.0000 - fn: 2128.0000 - accuracy: 0.9585 - precision: 0.9439 - recall: 0.9749 - auc: 0.9926 - prc: 0.9922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 4s - loss: 0.1144 - tp: 85706.0000 - fp: 5079.0000 - tn: 83134.0000 - fn: 2209.0000 - accuracy: 0.9586 - precision: 0.9441 - recall: 0.9749 - auc: 0.9926 - prc: 0.9922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 4s - loss: 0.1145 - tp: 88745.0000 - fp: 5270.0000 - tn: 85968.0000 - fn: 2289.0000 - accuracy: 0.9585 - precision: 0.9439 - recall: 0.9749 - auc: 0.9926 - prc: 0.9922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 4s - loss: 0.1145 - tp: 91807.0000 - fp: 5436.0000 - tn: 88820.0000 - fn: 2353.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9750 - auc: 0.9926 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 4s - loss: 0.1147 - tp: 94730.0000 - fp: 5626.0000 - tn: 91769.0000 - fn: 2435.0000 - accuracy: 0.9586 - precision: 0.9439 - recall: 0.9749 - auc: 0.9926 - prc: 0.9922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 4s - loss: 0.1147 - tp: 97732.0000 - fp: 5827.0000 - tn: 94631.0000 - fn: 2514.0000 - accuracy: 0.9584 - precision: 0.9437 - recall: 0.9749 - auc: 0.9926 - prc: 0.9922"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1146 - tp: 100703.0000 - fp: 5993.0000 - tn: 97553.0000 - fn: 2599.0000 - accuracy: 0.9585 - precision: 0.9438 - recall: 0.9748 - auc: 0.9926 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1145 - tp: 103693.0000 - fp: 6161.0000 - tn: 100455.0000 - fn: 2683.0000 - accuracy: 0.9585 - precision: 0.9439 - recall: 0.9748 - auc: 0.9926 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1144 - tp: 106815.0000 - fp: 6338.0000 - tn: 103230.0000 - fn: 2753.0000 - accuracy: 0.9585 - precision: 0.9440 - recall: 0.9749 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1143 - tp: 109808.0000 - fp: 6515.0000 - tn: 106132.0000 - fn: 2825.0000 - accuracy: 0.9585 - precision: 0.9440 - recall: 0.9749 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1142 - tp: 112845.0000 - fp: 6690.0000 - tn: 108990.0000 - fn: 2899.0000 - accuracy: 0.9586 - precision: 0.9440 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1142 - tp: 115902.0000 - fp: 6870.0000 - tn: 111822.0000 - fn: 2974.0000 - accuracy: 0.9586 - precision: 0.9440 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1142 - tp: 118886.0000 - fp: 7046.0000 - tn: 114731.0000 - fn: 3049.0000 - accuracy: 0.9586 - precision: 0.9440 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1140 - tp: 121892.0000 - fp: 7226.0000 - tn: 117618.0000 - fn: 3120.0000 - accuracy: 0.9586 - precision: 0.9440 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1141 - tp: 124924.0000 - fp: 7401.0000 - tn: 120468.0000 - fn: 3207.0000 - accuracy: 0.9586 - precision: 0.9441 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1140 - tp: 126909.0000 - fp: 7506.0000 - tn: 122419.0000 - fn: 3262.0000 - accuracy: 0.9586 - precision: 0.9442 - recall: 0.9749 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1140 - tp: 129840.0000 - fp: 7694.0000 - tn: 125372.0000 - fn: 3334.0000 - accuracy: 0.9586 - precision: 0.9441 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.1139 - tp: 132820.0000 - fp: 7884.0000 - tn: 128274.0000 - fn: 3406.0000 - accuracy: 0.9586 - precision: 0.9440 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/278 [=============>................] - ETA: 3s - loss: 0.1139 - tp: 135726.0000 - fp: 8067.0000 - tn: 131255.0000 - fn: 3480.0000 - accuracy: 0.9585 - precision: 0.9439 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.1137 - tp: 138768.0000 - fp: 8209.0000 - tn: 134144.0000 - fn: 3551.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.1137 - tp: 141809.0000 - fp: 8382.0000 - tn: 136995.0000 - fn: 3630.0000 - accuracy: 0.9587 - precision: 0.9442 - recall: 0.9750 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 3s - loss: 0.1136 - tp: 144787.0000 - fp: 8538.0000 - tn: 139937.0000 - fn: 3698.0000 - accuracy: 0.9588 - precision: 0.9443 - recall: 0.9751 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1138 - tp: 147777.0000 - fp: 8738.0000 - tn: 142806.0000 - fn: 3783.0000 - accuracy: 0.9587 - precision: 0.9442 - recall: 0.9750 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1138 - tp: 150756.0000 - fp: 8923.0000 - tn: 145717.0000 - fn: 3852.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9751 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1136 - tp: 153747.0000 - fp: 9101.0000 - tn: 148623.0000 - fn: 3921.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9751 - auc: 0.9927 - prc: 0.9923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "156/278 [===============>..............] - ETA: 2s - loss: 0.1136 - tp: 155737.0000 - fp: 9218.0000 - tn: 150558.0000 - fn: 3975.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9751 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "159/278 [================>.............] - ETA: 2s - loss: 0.1136 - tp: 158777.0000 - fp: 9377.0000 - tn: 153425.0000 - fn: 4053.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9751 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "162/278 [================>.............] - ETA: 2s - loss: 0.1136 - tp: 161787.0000 - fp: 9571.0000 - tn: 156287.0000 - fn: 4131.0000 - accuracy: 0.9587 - precision: 0.9441 - recall: 0.9751 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "165/278 [================>.............] - ETA: 2s - loss: 0.1136 - tp: 164823.0000 - fp: 9748.0000 - tn: 159149.0000 - fn: 4200.0000 - accuracy: 0.9587 - precision: 0.9442 - recall: 0.9752 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "168/278 [=================>............] - ETA: 2s - loss: 0.1135 - tp: 167717.0000 - fp: 9916.0000 - tn: 162161.0000 - fn: 4270.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "171/278 [=================>............] - ETA: 2s - loss: 0.1135 - tp: 170781.0000 - fp: 10089.0000 - tn: 164987.0000 - fn: 4351.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "174/278 [=================>............] - ETA: 2s - loss: 0.1135 - tp: 173749.0000 - fp: 10264.0000 - tn: 167924.0000 - fn: 4415.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "177/278 [==================>...........] - ETA: 2s - loss: 0.1135 - tp: 176749.0000 - fp: 10451.0000 - tn: 170810.0000 - fn: 4486.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "180/278 [==================>...........] - ETA: 2s - loss: 0.1135 - tp: 179758.0000 - fp: 10630.0000 - tn: 173689.0000 - fn: 4563.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "183/278 [==================>...........] - ETA: 2s - loss: 0.1135 - tp: 182748.0000 - fp: 10803.0000 - tn: 176587.0000 - fn: 4646.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "186/278 [===================>..........] - ETA: 2s - loss: 0.1135 - tp: 185791.0000 - fp: 10982.0000 - tn: 179439.0000 - fn: 4716.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "189/278 [===================>..........] - ETA: 2s - loss: 0.1135 - tp: 188863.0000 - fp: 11158.0000 - tn: 182253.0000 - fn: 4798.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9752 - auc: 0.9927 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "192/278 [===================>..........] - ETA: 1s - loss: 0.1134 - tp: 191859.0000 - fp: 11331.0000 - tn: 185160.0000 - fn: 4866.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "195/278 [====================>.........] - ETA: 1s - loss: 0.1134 - tp: 194945.0000 - fp: 11493.0000 - tn: 187984.0000 - fn: 4938.0000 - accuracy: 0.9589 - precision: 0.9443 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "198/278 [====================>.........] - ETA: 1s - loss: 0.1133 - tp: 197889.0000 - fp: 11676.0000 - tn: 190935.0000 - fn: 5004.0000 - accuracy: 0.9589 - precision: 0.9443 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "201/278 [====================>.........] - ETA: 1s - loss: 0.1133 - tp: 200840.0000 - fp: 11853.0000 - tn: 193872.0000 - fn: 5083.0000 - accuracy: 0.9589 - precision: 0.9443 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "204/278 [=====================>........] - ETA: 1s - loss: 0.1134 - tp: 203865.0000 - fp: 12042.0000 - tn: 196729.0000 - fn: 5156.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "207/278 [=====================>........] - ETA: 1s - loss: 0.1133 - tp: 206848.0000 - fp: 12219.0000 - tn: 199634.0000 - fn: 5235.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1133 - tp: 208878.0000 - fp: 12340.0000 - tn: 201526.0000 - fn: 5288.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9753 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1133 - tp: 211859.0000 - fp: 12529.0000 - tn: 204441.0000 - fn: 5347.0000 - accuracy: 0.9588 - precision: 0.9442 - recall: 0.9754 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1133 - tp: 214835.0000 - fp: 12690.0000 - tn: 207380.0000 - fn: 5415.0000 - accuracy: 0.9589 - precision: 0.9442 - recall: 0.9754 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1132 - tp: 217857.0000 - fp: 12837.0000 - tn: 210288.0000 - fn: 5482.0000 - accuracy: 0.9590 - precision: 0.9444 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.1132 - tp: 220915.0000 - fp: 13042.0000 - tn: 213097.0000 - fn: 5554.0000 - accuracy: 0.9589 - precision: 0.9443 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/278 [=======================>......] - ETA: 1s - loss: 0.1133 - tp: 223914.0000 - fp: 13238.0000 - tn: 215969.0000 - fn: 5631.0000 - accuracy: 0.9589 - precision: 0.9442 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "226/278 [=======================>......] - ETA: 1s - loss: 0.1132 - tp: 225869.0000 - fp: 13350.0000 - tn: 217950.0000 - fn: 5679.0000 - accuracy: 0.9589 - precision: 0.9442 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.1132 - tp: 228833.0000 - fp: 13547.0000 - tn: 220867.0000 - fn: 5745.0000 - accuracy: 0.9589 - precision: 0.9441 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.1131 - tp: 231819.0000 - fp: 13716.0000 - tn: 223787.0000 - fn: 5814.0000 - accuracy: 0.9589 - precision: 0.9441 - recall: 0.9755 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1130 - tp: 234920.0000 - fp: 13865.0000 - tn: 226616.0000 - fn: 5879.0000 - accuracy: 0.9590 - precision: 0.9443 - recall: 0.9756 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1130 - tp: 237959.0000 - fp: 14045.0000 - tn: 229470.0000 - fn: 5950.0000 - accuracy: 0.9590 - precision: 0.9443 - recall: 0.9756 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.1130 - tp: 240915.0000 - fp: 14226.0000 - tn: 232402.0000 - fn: 6025.0000 - accuracy: 0.9590 - precision: 0.9442 - recall: 0.9756 - auc: 0.9928 - prc: 0.9924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1129 - tp: 243912.0000 - fp: 14378.0000 - tn: 235339.0000 - fn: 6083.0000 - accuracy: 0.9591 - precision: 0.9443 - recall: 0.9757 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.1128 - tp: 246921.0000 - fp: 14540.0000 - tn: 238240.0000 - fn: 6155.0000 - accuracy: 0.9591 - precision: 0.9444 - recall: 0.9757 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.1128 - tp: 249880.0000 - fp: 14725.0000 - tn: 241167.0000 - fn: 6228.0000 - accuracy: 0.9591 - precision: 0.9444 - recall: 0.9757 - auc: 0.9929 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "253/278 [==========================>...] - ETA: 0s - loss: 0.1128 - tp: 252851.0000 - fp: 14915.0000 - tn: 244087.0000 - fn: 6291.0000 - accuracy: 0.9591 - precision: 0.9443 - recall: 0.9757 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "256/278 [==========================>...] - ETA: 0s - loss: 0.1127 - tp: 255884.0000 - fp: 15090.0000 - tn: 246950.0000 - fn: 6364.0000 - accuracy: 0.9591 - precision: 0.9443 - recall: 0.9757 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "259/278 [==========================>...] - ETA: 0s - loss: 0.1127 - tp: 258901.0000 - fp: 15280.0000 - tn: 249820.0000 - fn: 6431.0000 - accuracy: 0.9591 - precision: 0.9443 - recall: 0.9758 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "262/278 [===========================>..] - ETA: 0s - loss: 0.1127 - tp: 261926.0000 - fp: 15463.0000 - tn: 252691.0000 - fn: 6496.0000 - accuracy: 0.9591 - precision: 0.9443 - recall: 0.9758 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "265/278 [===========================>..] - ETA: 0s - loss: 0.1127 - tp: 264973.0000 - fp: 15649.0000 - tn: 255535.0000 - fn: 6563.0000 - accuracy: 0.9591 - precision: 0.9442 - recall: 0.9758 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "268/278 [===========================>..] - ETA: 0s - loss: 0.1127 - tp: 268048.0000 - fp: 15842.0000 - tn: 258347.0000 - fn: 6627.0000 - accuracy: 0.9591 - precision: 0.9442 - recall: 0.9759 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "271/278 [============================>.] - ETA: 0s - loss: 0.1127 - tp: 271061.0000 - fp: 16041.0000 - tn: 261204.0000 - fn: 6702.0000 - accuracy: 0.9590 - precision: 0.9441 - recall: 0.9759 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "274/278 [============================>.] - ETA: 0s - loss: 0.1127 - tp: 273996.0000 - fp: 16210.0000 - tn: 264179.0000 - fn: 6767.0000 - accuracy: 0.9591 - precision: 0.9441 - recall: 0.9759 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "277/278 [============================>.] - ETA: 0s - loss: 0.1126 - tp: 277051.0000 - fp: 16407.0000 - tn: 267000.0000 - fn: 6838.0000 - accuracy: 0.9590 - precision: 0.9441 - recall: 0.9759 - auc: 0.9928 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 7s 24ms/step - loss: 0.1126 - tp: 278043.0000 - fp: 16472.0000 - tn: 267971.0000 - fn: 6858.0000 - accuracy: 0.9590 - precision: 0.9441 - recall: 0.9759 - auc: 0.9928 - prc: 0.9925 - val_loss: 0.0407 - val_tp: 65.0000 - val_fp: 664.0000 - val_tn: 44836.0000 - val_fn: 4.0000 - val_accuracy: 0.9853 - val_precision: 0.0892 - val_recall: 0.9420 - val_auc: 0.9941 - val_prc: 0.7696\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1218 - tp: 990.0000 - fp: 58.0000 - tn: 976.0000 - fn: 24.0000 - accuracy: 0.9600 - precision: 0.9447 - recall: 0.9763 - auc: 0.9926 - prc: 0.9914"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/278 [..............................] - ETA: 5s - loss: 0.1122 - tp: 4023.0000 - fp: 246.0000 - tn: 3831.0000 - fn: 92.0000 - accuracy: 0.9587 - precision: 0.9424 - recall: 0.9776 - auc: 0.9931 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  6/278 [..............................] - ETA: 5s - loss: 0.1107 - tp: 6016.0000 - fp: 343.0000 - tn: 5787.0000 - fn: 142.0000 - accuracy: 0.9605 - precision: 0.9461 - recall: 0.9769 - auc: 0.9931 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 6s - loss: 0.1086 - tp: 8045.0000 - fp: 454.0000 - tn: 7701.0000 - fn: 184.0000 - accuracy: 0.9611 - precision: 0.9466 - recall: 0.9776 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/278 [>.............................] - ETA: 6s - loss: 0.1083 - tp: 10046.0000 - fp: 573.0000 - tn: 9635.0000 - fn: 226.0000 - accuracy: 0.9610 - precision: 0.9460 - recall: 0.9780 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 12/278 [>.............................] - ETA: 6s - loss: 0.1102 - tp: 12026.0000 - fp: 714.0000 - tn: 11572.0000 - fn: 264.0000 - accuracy: 0.9602 - precision: 0.9440 - recall: 0.9785 - auc: 0.9930 - prc: 0.9925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 6s - loss: 0.1104 - tp: 14052.0000 - fp: 822.0000 - tn: 13493.0000 - fn: 305.0000 - accuracy: 0.9607 - precision: 0.9447 - recall: 0.9788 - auc: 0.9930 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/278 [>.............................] - ETA: 6s - loss: 0.1098 - tp: 16055.0000 - fp: 939.0000 - tn: 15432.0000 - fn: 342.0000 - accuracy: 0.9609 - precision: 0.9447 - recall: 0.9791 - auc: 0.9932 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/278 [=>............................] - ETA: 6s - loss: 0.1087 - tp: 19077.0000 - fp: 1092.0000 - tn: 18340.0000 - fn: 403.0000 - accuracy: 0.9616 - precision: 0.9459 - recall: 0.9793 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/278 [=>............................] - ETA: 6s - loss: 0.1091 - tp: 22101.0000 - fp: 1277.0000 - tn: 21209.0000 - fn: 469.0000 - accuracy: 0.9612 - precision: 0.9454 - recall: 0.9792 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 6s - loss: 0.1090 - tp: 25164.0000 - fp: 1444.0000 - tn: 24059.0000 - fn: 533.0000 - accuracy: 0.9614 - precision: 0.9457 - recall: 0.9793 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 6s - loss: 0.1086 - tp: 28163.0000 - fp: 1611.0000 - tn: 26968.0000 - fn: 602.0000 - accuracy: 0.9614 - precision: 0.9459 - recall: 0.9791 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/278 [==>...........................] - ETA: 6s - loss: 0.1088 - tp: 31171.0000 - fp: 1805.0000 - tn: 29842.0000 - fn: 670.0000 - accuracy: 0.9610 - precision: 0.9453 - recall: 0.9790 - auc: 0.9932 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 33/278 [==>...........................] - ETA: 5s - loss: 0.1092 - tp: 33166.0000 - fp: 1923.0000 - tn: 31786.0000 - fn: 709.0000 - accuracy: 0.9611 - precision: 0.9452 - recall: 0.9791 - auc: 0.9932 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/278 [==>...........................] - ETA: 5s - loss: 0.1088 - tp: 36147.0000 - fp: 2084.0000 - tn: 34714.0000 - fn: 783.0000 - accuracy: 0.9611 - precision: 0.9455 - recall: 0.9788 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/278 [===>..........................] - ETA: 5s - loss: 0.1089 - tp: 39143.0000 - fp: 2261.0000 - tn: 37616.0000 - fn: 852.0000 - accuracy: 0.9610 - precision: 0.9454 - recall: 0.9787 - auc: 0.9932 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/278 [===>..........................] - ETA: 5s - loss: 0.1088 - tp: 42238.0000 - fp: 2425.0000 - tn: 40424.0000 - fn: 929.0000 - accuracy: 0.9610 - precision: 0.9457 - recall: 0.9785 - auc: 0.9931 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/278 [===>..........................] - ETA: 5s - loss: 0.1091 - tp: 45266.0000 - fp: 2629.0000 - tn: 43270.0000 - fn: 995.0000 - accuracy: 0.9607 - precision: 0.9451 - recall: 0.9785 - auc: 0.9931 - prc: 0.9926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/278 [====>.........................] - ETA: 5s - loss: 0.1087 - tp: 48264.0000 - fp: 2805.0000 - tn: 46180.0000 - fn: 1055.0000 - accuracy: 0.9607 - precision: 0.9451 - recall: 0.9786 - auc: 0.9932 - prc: 0.9927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/278 [====>.........................] - ETA: 5s - loss: 0.1085 - tp: 51289.0000 - fp: 2974.0000 - tn: 49080.0000 - fn: 1105.0000 - accuracy: 0.9609 - precision: 0.9452 - recall: 0.9789 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/278 [====>.........................] - ETA: 5s - loss: 0.1082 - tp: 54300.0000 - fp: 3131.0000 - tn: 51996.0000 - fn: 1165.0000 - accuracy: 0.9612 - precision: 0.9455 - recall: 0.9790 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 5s - loss: 0.1084 - tp: 56311.0000 - fp: 3258.0000 - tn: 53902.0000 - fn: 1217.0000 - accuracy: 0.9610 - precision: 0.9453 - recall: 0.9788 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 5s - loss: 0.1083 - tp: 59246.0000 - fp: 3431.0000 - tn: 56878.0000 - fn: 1277.0000 - accuracy: 0.9610 - precision: 0.9453 - recall: 0.9789 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 5s - loss: 0.1080 - tp: 62278.0000 - fp: 3590.0000 - tn: 59765.0000 - fn: 1343.0000 - accuracy: 0.9612 - precision: 0.9455 - recall: 0.9789 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 5s - loss: 0.1078 - tp: 65313.0000 - fp: 3749.0000 - tn: 62654.0000 - fn: 1404.0000 - accuracy: 0.9613 - precision: 0.9457 - recall: 0.9790 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 5s - loss: 0.1079 - tp: 68318.0000 - fp: 3926.0000 - tn: 65555.0000 - fn: 1465.0000 - accuracy: 0.9613 - precision: 0.9457 - recall: 0.9790 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1080 - tp: 71280.0000 - fp: 4106.0000 - tn: 68497.0000 - fn: 1525.0000 - accuracy: 0.9613 - precision: 0.9455 - recall: 0.9791 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1083 - tp: 74305.0000 - fp: 4306.0000 - tn: 71353.0000 - fn: 1588.0000 - accuracy: 0.9611 - precision: 0.9452 - recall: 0.9791 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.1084 - tp: 77291.0000 - fp: 4478.0000 - tn: 74274.0000 - fn: 1653.0000 - accuracy: 0.9611 - precision: 0.9452 - recall: 0.9791 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1084 - tp: 80252.0000 - fp: 4663.0000 - tn: 77202.0000 - fn: 1723.0000 - accuracy: 0.9610 - precision: 0.9451 - recall: 0.9790 - auc: 0.9932 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.1083 - tp: 83287.0000 - fp: 4836.0000 - tn: 80074.0000 - fn: 1787.0000 - accuracy: 0.9610 - precision: 0.9451 - recall: 0.9790 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 4s - loss: 0.1083 - tp: 86287.0000 - fp: 5020.0000 - tn: 82976.0000 - fn: 1845.0000 - accuracy: 0.9610 - precision: 0.9450 - recall: 0.9791 - auc: 0.9933 - prc: 0.9928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 4s - loss: 0.1081 - tp: 89310.0000 - fp: 5183.0000 - tn: 85876.0000 - fn: 1903.0000 - accuracy: 0.9611 - precision: 0.9451 - recall: 0.9791 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 4s - loss: 0.1081 - tp: 92329.0000 - fp: 5343.0000 - tn: 88777.0000 - fn: 1967.0000 - accuracy: 0.9612 - precision: 0.9453 - recall: 0.9791 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 4s - loss: 0.1080 - tp: 95332.0000 - fp: 5521.0000 - tn: 91686.0000 - fn: 2021.0000 - accuracy: 0.9612 - precision: 0.9453 - recall: 0.9792 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 4s - loss: 0.1079 - tp: 97307.0000 - fp: 5640.0000 - tn: 93654.0000 - fn: 2055.0000 - accuracy: 0.9613 - precision: 0.9452 - recall: 0.9793 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 4s - loss: 0.1080 - tp: 100275.0000 - fp: 5822.0000 - tn: 96587.0000 - fn: 2116.0000 - accuracy: 0.9612 - precision: 0.9451 - recall: 0.9793 - auc: 0.9933 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 4s - loss: 0.1079 - tp: 103274.0000 - fp: 5974.0000 - tn: 99520.0000 - fn: 2176.0000 - accuracy: 0.9614 - precision: 0.9453 - recall: 0.9794 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 4s - loss: 0.1076 - tp: 106218.0000 - fp: 6134.0000 - tn: 102499.0000 - fn: 2237.0000 - accuracy: 0.9614 - precision: 0.9454 - recall: 0.9794 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 4s - loss: 0.1077 - tp: 109150.0000 - fp: 6326.0000 - tn: 105460.0000 - fn: 2296.0000 - accuracy: 0.9614 - precision: 0.9452 - recall: 0.9794 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.1077 - tp: 112204.0000 - fp: 6503.0000 - tn: 108317.0000 - fn: 2352.0000 - accuracy: 0.9614 - precision: 0.9452 - recall: 0.9795 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.1076 - tp: 115203.0000 - fp: 6671.0000 - tn: 111242.0000 - fn: 2404.0000 - accuracy: 0.9615 - precision: 0.9453 - recall: 0.9796 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1075 - tp: 118244.0000 - fp: 6834.0000 - tn: 114115.0000 - fn: 2471.0000 - accuracy: 0.9615 - precision: 0.9454 - recall: 0.9795 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1074 - tp: 121256.0000 - fp: 6998.0000 - tn: 117026.0000 - fn: 2528.0000 - accuracy: 0.9616 - precision: 0.9454 - recall: 0.9796 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.1076 - tp: 124149.0000 - fp: 7195.0000 - tn: 120024.0000 - fn: 2584.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9796 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1076 - tp: 127110.0000 - fp: 7356.0000 - tn: 122989.0000 - fn: 2641.0000 - accuracy: 0.9616 - precision: 0.9453 - recall: 0.9796 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1075 - tp: 130110.0000 - fp: 7525.0000 - tn: 125894.0000 - fn: 2711.0000 - accuracy: 0.9616 - precision: 0.9453 - recall: 0.9796 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "132/278 [=============>................] - ETA: 3s - loss: 0.1075 - tp: 132157.0000 - fp: 7647.0000 - tn: 127777.0000 - fn: 2755.0000 - accuracy: 0.9615 - precision: 0.9453 - recall: 0.9796 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 3s - loss: 0.1076 - tp: 134171.0000 - fp: 7783.0000 - tn: 129687.0000 - fn: 2791.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9796 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.1075 - tp: 137203.0000 - fp: 7966.0000 - tn: 132561.0000 - fn: 2846.0000 - accuracy: 0.9615 - precision: 0.9451 - recall: 0.9797 - auc: 0.9934 - prc: 0.9929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/278 [==============>...............] - ETA: 3s - loss: 0.1074 - tp: 140112.0000 - fp: 8129.0000 - tn: 135571.0000 - fn: 2908.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9797 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "143/278 [==============>...............] - ETA: 3s - loss: 0.1073 - tp: 143155.0000 - fp: 8306.0000 - tn: 138439.0000 - fn: 2964.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9797 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/278 [==============>...............] - ETA: 3s - loss: 0.1073 - tp: 146171.0000 - fp: 8472.0000 - tn: 141337.0000 - fn: 3028.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9797 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/278 [===============>..............] - ETA: 3s - loss: 0.1073 - tp: 149175.0000 - fp: 8638.0000 - tn: 144247.0000 - fn: 3092.0000 - accuracy: 0.9616 - precision: 0.9453 - recall: 0.9797 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1072 - tp: 152116.0000 - fp: 8791.0000 - tn: 147239.0000 - fn: 3150.0000 - accuracy: 0.9616 - precision: 0.9454 - recall: 0.9797 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1072 - tp: 155238.0000 - fp: 8976.0000 - tn: 150022.0000 - fn: 3204.0000 - accuracy: 0.9616 - precision: 0.9453 - recall: 0.9798 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1073 - tp: 158205.0000 - fp: 9177.0000 - tn: 152936.0000 - fn: 3266.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9798 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1073 - tp: 161200.0000 - fp: 9362.0000 - tn: 155844.0000 - fn: 3322.0000 - accuracy: 0.9615 - precision: 0.9451 - recall: 0.9798 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1072 - tp: 164215.0000 - fp: 9542.0000 - tn: 158726.0000 - fn: 3389.0000 - accuracy: 0.9615 - precision: 0.9451 - recall: 0.9798 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1072 - tp: 167226.0000 - fp: 9704.0000 - tn: 161635.0000 - fn: 3451.0000 - accuracy: 0.9615 - precision: 0.9452 - recall: 0.9798 - auc: 0.9934 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1070 - tp: 170223.0000 - fp: 9858.0000 - tn: 164577.0000 - fn: 3502.0000 - accuracy: 0.9616 - precision: 0.9453 - recall: 0.9798 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1071 - tp: 173189.0000 - fp: 10060.0000 - tn: 167501.0000 - fn: 3554.0000 - accuracy: 0.9616 - precision: 0.9451 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1070 - tp: 176148.0000 - fp: 10242.0000 - tn: 170450.0000 - fn: 3608.0000 - accuracy: 0.9616 - precision: 0.9451 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1069 - tp: 179168.0000 - fp: 10396.0000 - tn: 173364.0000 - fn: 3664.0000 - accuracy: 0.9616 - precision: 0.9452 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.1068 - tp: 182133.0000 - fp: 10578.0000 - tn: 176295.0000 - fn: 3730.0000 - accuracy: 0.9616 - precision: 0.9451 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.1068 - tp: 185220.0000 - fp: 10773.0000 - tn: 179095.0000 - fn: 3792.0000 - accuracy: 0.9616 - precision: 0.9450 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "188/278 [===================>..........] - ETA: 2s - loss: 0.1068 - tp: 188196.0000 - fp: 10944.0000 - tn: 182035.0000 - fn: 3849.0000 - accuracy: 0.9616 - precision: 0.9450 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/278 [===================>..........] - ETA: 2s - loss: 0.1068 - tp: 191242.0000 - fp: 11120.0000 - tn: 184890.0000 - fn: 3916.0000 - accuracy: 0.9616 - precision: 0.9450 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1068 - tp: 194247.0000 - fp: 11300.0000 - tn: 187783.0000 - fn: 3982.0000 - accuracy: 0.9615 - precision: 0.9450 - recall: 0.9799 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.1068 - tp: 197251.0000 - fp: 11481.0000 - tn: 190692.0000 - fn: 4032.0000 - accuracy: 0.9615 - precision: 0.9450 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.1068 - tp: 200208.0000 - fp: 11656.0000 - tn: 193641.0000 - fn: 4095.0000 - accuracy: 0.9615 - precision: 0.9450 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.1067 - tp: 203142.0000 - fp: 11841.0000 - tn: 196614.0000 - fn: 4147.0000 - accuracy: 0.9615 - precision: 0.9449 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.1067 - tp: 206158.0000 - fp: 12016.0000 - tn: 199521.0000 - fn: 4193.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9801 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1068 - tp: 209095.0000 - fp: 12216.0000 - tn: 202466.0000 - fn: 4255.0000 - accuracy: 0.9615 - precision: 0.9448 - recall: 0.9801 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1067 - tp: 212098.0000 - fp: 12379.0000 - tn: 205390.0000 - fn: 4309.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9801 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1067 - tp: 215131.0000 - fp: 12537.0000 - tn: 208288.0000 - fn: 4364.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9801 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1066 - tp: 218118.0000 - fp: 12693.0000 - tn: 211227.0000 - fn: 4426.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9801 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.1066 - tp: 221135.0000 - fp: 12876.0000 - tn: 214121.0000 - fn: 4476.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/278 [=======================>......] - ETA: 1s - loss: 0.1067 - tp: 224123.0000 - fp: 13066.0000 - tn: 217031.0000 - fn: 4532.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "227/278 [=======================>......] - ETA: 1s - loss: 0.1067 - tp: 227123.0000 - fp: 13224.0000 - tn: 219961.0000 - fn: 4588.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "230/278 [=======================>......] - ETA: 1s - loss: 0.1067 - tp: 230106.0000 - fp: 13410.0000 - tn: 222874.0000 - fn: 4650.0000 - accuracy: 0.9617 - precision: 0.9449 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "233/278 [========================>.....] - ETA: 1s - loss: 0.1067 - tp: 233153.0000 - fp: 13590.0000 - tn: 225727.0000 - fn: 4714.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "236/278 [========================>.....] - ETA: 0s - loss: 0.1066 - tp: 236116.0000 - fp: 13779.0000 - tn: 228674.0000 - fn: 4759.0000 - accuracy: 0.9616 - precision: 0.9449 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "239/278 [========================>.....] - ETA: 0s - loss: 0.1065 - tp: 239201.0000 - fp: 13936.0000 - tn: 231512.0000 - fn: 4823.0000 - accuracy: 0.9617 - precision: 0.9449 - recall: 0.9802 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.1065 - tp: 241199.0000 - fp: 14051.0000 - tn: 233462.0000 - fn: 4856.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9803 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1065 - tp: 244270.0000 - fp: 14215.0000 - tn: 236314.0000 - fn: 4913.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9803 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.1065 - tp: 247237.0000 - fp: 14412.0000 - tn: 239234.0000 - fn: 4973.0000 - accuracy: 0.9617 - precision: 0.9449 - recall: 0.9803 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.1065 - tp: 250271.0000 - fp: 14572.0000 - tn: 242142.0000 - fn: 5015.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9804 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1065 - tp: 252302.0000 - fp: 14686.0000 - tn: 244050.0000 - fn: 5058.0000 - accuracy: 0.9617 - precision: 0.9450 - recall: 0.9803 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1064 - tp: 255222.0000 - fp: 14852.0000 - tn: 247049.0000 - fn: 5117.0000 - accuracy: 0.9618 - precision: 0.9450 - recall: 0.9803 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1063 - tp: 258228.0000 - fp: 15010.0000 - tn: 249968.0000 - fn: 5178.0000 - accuracy: 0.9618 - precision: 0.9451 - recall: 0.9803 - auc: 0.9935 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1062 - tp: 261259.0000 - fp: 15156.0000 - tn: 252875.0000 - fn: 5238.0000 - accuracy: 0.9618 - precision: 0.9452 - recall: 0.9803 - auc: 0.9935 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1062 - tp: 264268.0000 - fp: 15335.0000 - tn: 255778.0000 - fn: 5291.0000 - accuracy: 0.9619 - precision: 0.9452 - recall: 0.9804 - auc: 0.9935 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1062 - tp: 267228.0000 - fp: 15503.0000 - tn: 258731.0000 - fn: 5354.0000 - accuracy: 0.9619 - precision: 0.9452 - recall: 0.9804 - auc: 0.9935 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1061 - tp: 270272.0000 - fp: 15662.0000 - tn: 261611.0000 - fn: 5415.0000 - accuracy: 0.9619 - precision: 0.9452 - recall: 0.9804 - auc: 0.9936 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1061 - tp: 273269.0000 - fp: 15823.0000 - tn: 264533.0000 - fn: 5479.0000 - accuracy: 0.9619 - precision: 0.9453 - recall: 0.9803 - auc: 0.9936 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1060 - tp: 276205.0000 - fp: 15989.0000 - tn: 267513.0000 - fn: 5541.0000 - accuracy: 0.9619 - precision: 0.9453 - recall: 0.9803 - auc: 0.9936 - prc: 0.9931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 7s 24ms/step - loss: 0.1061 - tp: 278163.0000 - fp: 16128.0000 - tn: 269479.0000 - fn: 5574.0000 - accuracy: 0.9619 - precision: 0.9452 - recall: 0.9804 - auc: 0.9936 - prc: 0.9931 - val_loss: 0.0370 - val_tp: 65.0000 - val_fp: 620.0000 - val_tn: 44880.0000 - val_fn: 4.0000 - val_accuracy: 0.9863 - val_precision: 0.0949 - val_recall: 0.9420 - val_auc: 0.9935 - val_prc: 0.7715\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1063 - tp: 999.0000 - fp: 73.0000 - tn: 957.0000 - fn: 19.0000 - accuracy: 0.9551 - precision: 0.9319 - recall: 0.9813 - auc: 0.9933 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1039 - tp: 4944.0000 - fp: 315.0000 - tn: 4880.0000 - fn: 101.0000 - accuracy: 0.9594 - precision: 0.9401 - recall: 0.9800 - auc: 0.9935 - prc: 0.9930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1029 - tp: 7997.0000 - fp: 474.0000 - tn: 7749.0000 - fn: 164.0000 - accuracy: 0.9611 - precision: 0.9440 - recall: 0.9799 - auc: 0.9938 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1017 - tp: 10966.0000 - fp: 631.0000 - tn: 10721.0000 - fn: 210.0000 - accuracy: 0.9627 - precision: 0.9456 - recall: 0.9812 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1020 - tp: 14004.0000 - fp: 802.0000 - tn: 13605.0000 - fn: 261.0000 - accuracy: 0.9629 - precision: 0.9458 - recall: 0.9817 - auc: 0.9940 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1006 - tp: 17080.0000 - fp: 940.0000 - tn: 16486.0000 - fn: 310.0000 - accuracy: 0.9641 - precision: 0.9478 - recall: 0.9822 - auc: 0.9941 - prc: 0.9938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/278 [=>............................] - ETA: 5s - loss: 0.1010 - tp: 19036.0000 - fp: 1064.0000 - tn: 18468.0000 - fn: 344.0000 - accuracy: 0.9638 - precision: 0.9471 - recall: 0.9822 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/278 [=>............................] - ETA: 5s - loss: 0.1008 - tp: 22034.0000 - fp: 1233.0000 - tn: 21395.0000 - fn: 394.0000 - accuracy: 0.9639 - precision: 0.9470 - recall: 0.9824 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1018 - tp: 25085.0000 - fp: 1444.0000 - tn: 24222.0000 - fn: 449.0000 - accuracy: 0.9630 - precision: 0.9456 - recall: 0.9824 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1022 - tp: 28065.0000 - fp: 1640.0000 - tn: 27138.0000 - fn: 501.0000 - accuracy: 0.9627 - precision: 0.9448 - recall: 0.9825 - auc: 0.9938 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/278 [==>...........................] - ETA: 5s - loss: 0.1024 - tp: 31108.0000 - fp: 1803.0000 - tn: 30017.0000 - fn: 560.0000 - accuracy: 0.9628 - precision: 0.9452 - recall: 0.9823 - auc: 0.9938 - prc: 0.9933"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.1021 - tp: 34073.0000 - fp: 1977.0000 - tn: 32959.0000 - fn: 623.0000 - accuracy: 0.9627 - precision: 0.9452 - recall: 0.9820 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/278 [==>...........................] - ETA: 5s - loss: 0.1020 - tp: 37045.0000 - fp: 2160.0000 - tn: 35881.0000 - fn: 690.0000 - accuracy: 0.9624 - precision: 0.9449 - recall: 0.9817 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/278 [===>..........................] - ETA: 5s - loss: 0.1019 - tp: 40024.0000 - fp: 2324.0000 - tn: 38823.0000 - fn: 749.0000 - accuracy: 0.9625 - precision: 0.9451 - recall: 0.9816 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/278 [===>..........................] - ETA: 5s - loss: 0.1020 - tp: 43065.0000 - fp: 2485.0000 - tn: 41705.0000 - fn: 809.0000 - accuracy: 0.9626 - precision: 0.9454 - recall: 0.9816 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/278 [===>..........................] - ETA: 5s - loss: 0.1021 - tp: 46062.0000 - fp: 2671.0000 - tn: 44615.0000 - fn: 860.0000 - accuracy: 0.9625 - precision: 0.9452 - recall: 0.9817 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/278 [====>.........................] - ETA: 5s - loss: 0.1019 - tp: 49068.0000 - fp: 2840.0000 - tn: 47523.0000 - fn: 921.0000 - accuracy: 0.9625 - precision: 0.9453 - recall: 0.9816 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/278 [====>.........................] - ETA: 5s - loss: 0.1021 - tp: 52063.0000 - fp: 3029.0000 - tn: 50431.0000 - fn: 973.0000 - accuracy: 0.9624 - precision: 0.9450 - recall: 0.9817 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/278 [====>.........................] - ETA: 4s - loss: 0.1020 - tp: 55085.0000 - fp: 3197.0000 - tn: 53334.0000 - fn: 1024.0000 - accuracy: 0.9625 - precision: 0.9451 - recall: 0.9817 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/278 [=====>........................] - ETA: 4s - loss: 0.1019 - tp: 58188.0000 - fp: 3370.0000 - tn: 56149.0000 - fn: 1077.0000 - accuracy: 0.9626 - precision: 0.9453 - recall: 0.9818 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/278 [=====>........................] - ETA: 4s - loss: 0.1022 - tp: 61227.0000 - fp: 3566.0000 - tn: 58994.0000 - fn: 1141.0000 - accuracy: 0.9623 - precision: 0.9450 - recall: 0.9817 - auc: 0.9939 - prc: 0.9934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 64/278 [=====>........................] - ETA: 4s - loss: 0.1019 - tp: 64212.0000 - fp: 3725.0000 - tn: 61938.0000 - fn: 1197.0000 - accuracy: 0.9624 - precision: 0.9452 - recall: 0.9817 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/278 [======>.......................] - ETA: 4s - loss: 0.1017 - tp: 67204.0000 - fp: 3881.0000 - tn: 64882.0000 - fn: 1249.0000 - accuracy: 0.9626 - precision: 0.9454 - recall: 0.9818 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/278 [======>.......................] - ETA: 4s - loss: 0.1019 - tp: 70226.0000 - fp: 4057.0000 - tn: 67772.0000 - fn: 1305.0000 - accuracy: 0.9626 - precision: 0.9454 - recall: 0.9818 - auc: 0.9939 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/278 [======>.......................] - ETA: 4s - loss: 0.1019 - tp: 73302.0000 - fp: 4227.0000 - tn: 70627.0000 - fn: 1348.0000 - accuracy: 0.9627 - precision: 0.9455 - recall: 0.9819 - auc: 0.9940 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 76/278 [=======>......................] - ETA: 4s - loss: 0.1018 - tp: 76282.0000 - fp: 4396.0000 - tn: 73569.0000 - fn: 1401.0000 - accuracy: 0.9628 - precision: 0.9455 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 0.1016 - tp: 79247.0000 - fp: 4571.0000 - tn: 76524.0000 - fn: 1450.0000 - accuracy: 0.9628 - precision: 0.9455 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/278 [=======>......................] - ETA: 4s - loss: 0.1017 - tp: 82236.0000 - fp: 4778.0000 - tn: 79416.0000 - fn: 1506.0000 - accuracy: 0.9626 - precision: 0.9451 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 0.1016 - tp: 85245.0000 - fp: 4961.0000 - tn: 82311.0000 - fn: 1563.0000 - accuracy: 0.9625 - precision: 0.9450 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/278 [========>.....................] - ETA: 4s - loss: 0.1016 - tp: 88297.0000 - fp: 5132.0000 - tn: 85180.0000 - fn: 1615.0000 - accuracy: 0.9626 - precision: 0.9451 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/278 [========>.....................] - ETA: 4s - loss: 0.1017 - tp: 91261.0000 - fp: 5306.0000 - tn: 88124.0000 - fn: 1677.0000 - accuracy: 0.9625 - precision: 0.9451 - recall: 0.9820 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/278 [=========>....................] - ETA: 4s - loss: 0.1017 - tp: 94273.0000 - fp: 5488.0000 - tn: 91018.0000 - fn: 1733.0000 - accuracy: 0.9625 - precision: 0.9450 - recall: 0.9819 - auc: 0.9940 - prc: 0.9935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 4s - loss: 0.1016 - tp: 97285.0000 - fp: 5627.0000 - tn: 93945.0000 - fn: 1799.0000 - accuracy: 0.9626 - precision: 0.9453 - recall: 0.9818 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 4s - loss: 0.1015 - tp: 100298.0000 - fp: 5798.0000 - tn: 96856.0000 - fn: 1848.0000 - accuracy: 0.9627 - precision: 0.9454 - recall: 0.9819 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 0.1016 - tp: 103306.0000 - fp: 5964.0000 - tn: 99771.0000 - fn: 1903.0000 - accuracy: 0.9627 - precision: 0.9454 - recall: 0.9819 - auc: 0.9940 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.1014 - tp: 106268.0000 - fp: 6126.0000 - tn: 102743.0000 - fn: 1951.0000 - accuracy: 0.9628 - precision: 0.9455 - recall: 0.9820 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.1012 - tp: 109278.0000 - fp: 6289.0000 - tn: 105671.0000 - fn: 1994.0000 - accuracy: 0.9629 - precision: 0.9456 - recall: 0.9821 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.1012 - tp: 112318.0000 - fp: 6458.0000 - tn: 108545.0000 - fn: 2055.0000 - accuracy: 0.9629 - precision: 0.9456 - recall: 0.9820 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.1010 - tp: 115364.0000 - fp: 6598.0000 - tn: 111441.0000 - fn: 2117.0000 - accuracy: 0.9630 - precision: 0.9459 - recall: 0.9820 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1012 - tp: 118364.0000 - fp: 6784.0000 - tn: 114347.0000 - fn: 2169.0000 - accuracy: 0.9630 - precision: 0.9458 - recall: 0.9820 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1011 - tp: 121361.0000 - fp: 6950.0000 - tn: 117278.0000 - fn: 2219.0000 - accuracy: 0.9630 - precision: 0.9458 - recall: 0.9820 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.1009 - tp: 124332.0000 - fp: 7099.0000 - tn: 120252.0000 - fn: 2269.0000 - accuracy: 0.9631 - precision: 0.9460 - recall: 0.9821 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1010 - tp: 127379.0000 - fp: 7283.0000 - tn: 123112.0000 - fn: 2322.0000 - accuracy: 0.9631 - precision: 0.9459 - recall: 0.9821 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1010 - tp: 130390.0000 - fp: 7456.0000 - tn: 126016.0000 - fn: 2378.0000 - accuracy: 0.9631 - precision: 0.9459 - recall: 0.9821 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.1010 - tp: 133369.0000 - fp: 7653.0000 - tn: 128931.0000 - fn: 2431.0000 - accuracy: 0.9630 - precision: 0.9457 - recall: 0.9821 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/278 [=============>................] - ETA: 3s - loss: 0.1011 - tp: 136408.0000 - fp: 7838.0000 - tn: 131809.0000 - fn: 2473.0000 - accuracy: 0.9630 - precision: 0.9457 - recall: 0.9822 - auc: 0.9941 - prc: 0.9936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.1008 - tp: 139446.0000 - fp: 8001.0000 - tn: 134711.0000 - fn: 2514.0000 - accuracy: 0.9631 - precision: 0.9457 - recall: 0.9823 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.1008 - tp: 142505.0000 - fp: 8158.0000 - tn: 137591.0000 - fn: 2562.0000 - accuracy: 0.9631 - precision: 0.9459 - recall: 0.9823 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 3s - loss: 0.1007 - tp: 145518.0000 - fp: 8309.0000 - tn: 140522.0000 - fn: 2611.0000 - accuracy: 0.9632 - precision: 0.9460 - recall: 0.9824 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1007 - tp: 148490.0000 - fp: 8494.0000 - tn: 143461.0000 - fn: 2659.0000 - accuracy: 0.9632 - precision: 0.9459 - recall: 0.9824 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1006 - tp: 151496.0000 - fp: 8656.0000 - tn: 146383.0000 - fn: 2713.0000 - accuracy: 0.9632 - precision: 0.9460 - recall: 0.9824 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1006 - tp: 154530.0000 - fp: 8834.0000 - tn: 149263.0000 - fn: 2765.0000 - accuracy: 0.9632 - precision: 0.9459 - recall: 0.9824 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.1006 - tp: 157552.0000 - fp: 9004.0000 - tn: 152171.0000 - fn: 2809.0000 - accuracy: 0.9633 - precision: 0.9459 - recall: 0.9825 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "159/278 [================>.............] - ETA: 2s - loss: 0.1005 - tp: 159556.0000 - fp: 9104.0000 - tn: 154126.0000 - fn: 2846.0000 - accuracy: 0.9633 - precision: 0.9460 - recall: 0.9825 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "162/278 [================>.............] - ETA: 2s - loss: 0.1006 - tp: 162574.0000 - fp: 9284.0000 - tn: 157023.0000 - fn: 2895.0000 - accuracy: 0.9633 - precision: 0.9460 - recall: 0.9825 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "165/278 [================>.............] - ETA: 2s - loss: 0.1005 - tp: 165580.0000 - fp: 9429.0000 - tn: 159970.0000 - fn: 2941.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9825 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "168/278 [=================>............] - ETA: 2s - loss: 0.1004 - tp: 168609.0000 - fp: 9601.0000 - tn: 162869.0000 - fn: 2985.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9826 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "171/278 [=================>............] - ETA: 2s - loss: 0.1004 - tp: 171655.0000 - fp: 9771.0000 - tn: 165746.0000 - fn: 3036.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9826 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1004 - tp: 173612.0000 - fp: 9879.0000 - tn: 167739.0000 - fn: 3074.0000 - accuracy: 0.9634 - precision: 0.9462 - recall: 0.9826 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1004 - tp: 176626.0000 - fp: 10071.0000 - tn: 170632.0000 - fn: 3119.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9826 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1004 - tp: 179660.0000 - fp: 10234.0000 - tn: 173520.0000 - fn: 3178.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9826 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.1004 - tp: 182647.0000 - fp: 10423.0000 - tn: 176437.0000 - fn: 3229.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9826 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 2s - loss: 0.1004 - tp: 185678.0000 - fp: 10591.0000 - tn: 179334.0000 - fn: 3277.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9827 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "188/278 [===================>..........] - ETA: 2s - loss: 0.1004 - tp: 188686.0000 - fp: 10759.0000 - tn: 182249.0000 - fn: 3330.0000 - accuracy: 0.9634 - precision: 0.9461 - recall: 0.9827 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1004 - tp: 191685.0000 - fp: 10951.0000 - tn: 185157.0000 - fn: 3375.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9827 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1004 - tp: 194690.0000 - fp: 11143.0000 - tn: 188057.0000 - fn: 3422.0000 - accuracy: 0.9633 - precision: 0.9459 - recall: 0.9827 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.1004 - tp: 197691.0000 - fp: 11314.0000 - tn: 190973.0000 - fn: 3478.0000 - accuracy: 0.9633 - precision: 0.9459 - recall: 0.9827 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.1003 - tp: 200678.0000 - fp: 11470.0000 - tn: 193929.0000 - fn: 3523.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9827 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.1004 - tp: 203704.0000 - fp: 11665.0000 - tn: 196803.0000 - fn: 3572.0000 - accuracy: 0.9634 - precision: 0.9458 - recall: 0.9828 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.1004 - tp: 205711.0000 - fp: 11775.0000 - tn: 198751.0000 - fn: 3603.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.1003 - tp: 208718.0000 - fp: 11938.0000 - tn: 201676.0000 - fn: 3652.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "210/278 [=====================>........] - ETA: 1s - loss: 0.1003 - tp: 210692.0000 - fp: 12056.0000 - tn: 203652.0000 - fn: 3680.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.1003 - tp: 213648.0000 - fp: 12224.0000 - tn: 206613.0000 - fn: 3739.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1002 - tp: 215646.0000 - fp: 12326.0000 - tn: 208576.0000 - fn: 3772.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1002 - tp: 218625.0000 - fp: 12491.0000 - tn: 211519.0000 - fn: 3829.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "221/278 [======================>.......] - ETA: 1s - loss: 0.1002 - tp: 221601.0000 - fp: 12660.0000 - tn: 214458.0000 - fn: 3889.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/278 [=======================>......] - ETA: 1s - loss: 0.1001 - tp: 224624.0000 - fp: 12832.0000 - tn: 217356.0000 - fn: 3940.0000 - accuracy: 0.9634 - precision: 0.9460 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "227/278 [=======================>......] - ETA: 1s - loss: 0.1002 - tp: 227637.0000 - fp: 13010.0000 - tn: 220260.0000 - fn: 3989.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9941 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "230/278 [=======================>......] - ETA: 1s - loss: 0.1001 - tp: 230600.0000 - fp: 13185.0000 - tn: 223215.0000 - fn: 4040.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.1001 - tp: 232604.0000 - fp: 13303.0000 - tn: 225150.0000 - fn: 4079.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1001 - tp: 235596.0000 - fp: 13474.0000 - tn: 228086.0000 - fn: 4124.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1000 - tp: 238611.0000 - fp: 13643.0000 - tn: 231000.0000 - fn: 4170.0000 - accuracy: 0.9635 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.1000 - tp: 241573.0000 - fp: 13824.0000 - tn: 233948.0000 - fn: 4223.0000 - accuracy: 0.9634 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1000 - tp: 244633.0000 - fp: 13986.0000 - tn: 236823.0000 - fn: 4270.0000 - accuracy: 0.9635 - precision: 0.9459 - recall: 0.9828 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.0999 - tp: 247656.0000 - fp: 14132.0000 - tn: 239756.0000 - fn: 4312.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.0998 - tp: 249702.0000 - fp: 14246.0000 - tn: 241663.0000 - fn: 4341.0000 - accuracy: 0.9636 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.0998 - tp: 252738.0000 - fp: 14418.0000 - tn: 244540.0000 - fn: 4400.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "254/278 [==========================>...] - ETA: 0s - loss: 0.0999 - tp: 254719.0000 - fp: 14543.0000 - tn: 246504.0000 - fn: 4426.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "257/278 [==========================>...] - ETA: 0s - loss: 0.0999 - tp: 257756.0000 - fp: 14714.0000 - tn: 249391.0000 - fn: 4475.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "260/278 [===========================>..] - ETA: 0s - loss: 0.0998 - tp: 260817.0000 - fp: 14894.0000 - tn: 252245.0000 - fn: 4524.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9830 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "263/278 [===========================>..] - ETA: 0s - loss: 0.0998 - tp: 263816.0000 - fp: 15060.0000 - tn: 255171.0000 - fn: 4577.0000 - accuracy: 0.9635 - precision: 0.9460 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "266/278 [===========================>..] - ETA: 0s - loss: 0.0997 - tp: 266837.0000 - fp: 15223.0000 - tn: 258082.0000 - fn: 4626.0000 - accuracy: 0.9636 - precision: 0.9460 - recall: 0.9830 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "269/278 [============================>.] - ETA: 0s - loss: 0.0997 - tp: 269924.0000 - fp: 15395.0000 - tn: 260916.0000 - fn: 4677.0000 - accuracy: 0.9636 - precision: 0.9460 - recall: 0.9830 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "272/278 [============================>.] - ETA: 0s - loss: 0.0997 - tp: 272967.0000 - fp: 15560.0000 - tn: 263800.0000 - fn: 4729.0000 - accuracy: 0.9636 - precision: 0.9461 - recall: 0.9830 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "275/278 [============================>.] - ETA: 0s - loss: 0.0997 - tp: 275975.0000 - fp: 15714.0000 - tn: 266729.0000 - fn: 4782.0000 - accuracy: 0.9636 - precision: 0.9461 - recall: 0.9830 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - ETA: 0s - loss: 0.0997 - tp: 278905.0000 - fp: 15891.0000 - tn: 269709.0000 - fn: 4839.0000 - accuracy: 0.9636 - precision: 0.9461 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.0997 - tp: 278905.0000 - fp: 15891.0000 - tn: 269709.0000 - fn: 4839.0000 - accuracy: 0.9636 - precision: 0.9461 - recall: 0.9829 - auc: 0.9942 - prc: 0.9937 - val_loss: 0.0342 - val_tp: 65.0000 - val_fp: 585.0000 - val_tn: 44915.0000 - val_fn: 4.0000 - val_accuracy: 0.9871 - val_precision: 0.1000 - val_recall: 0.9420 - val_auc: 0.9931 - val_prc: 0.7760\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.0997 - tp: 1020.0000 - fp: 57.0000 - tn: 958.0000 - fn: 13.0000 - accuracy: 0.9658 - precision: 0.9471 - recall: 0.9874 - auc: 0.9946 - prc: 0.9945"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.0953 - tp: 5082.0000 - fp: 268.0000 - tn: 4809.0000 - fn: 81.0000 - accuracy: 0.9659 - precision: 0.9499 - recall: 0.9843 - auc: 0.9946 - prc: 0.9943"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.0953 - tp: 8077.0000 - fp: 444.0000 - tn: 7729.0000 - fn: 134.0000 - accuracy: 0.9647 - precision: 0.9479 - recall: 0.9837 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.0968 - tp: 11105.0000 - fp: 648.0000 - tn: 10597.0000 - fn: 178.0000 - accuracy: 0.9633 - precision: 0.9449 - recall: 0.9842 - auc: 0.9943 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.0977 - tp: 14156.0000 - fp: 832.0000 - tn: 13453.0000 - fn: 231.0000 - accuracy: 0.9629 - precision: 0.9445 - recall: 0.9839 - auc: 0.9941 - prc: 0.9939"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.0965 - tp: 17135.0000 - fp: 993.0000 - tn: 16412.0000 - fn: 276.0000 - accuracy: 0.9636 - precision: 0.9452 - recall: 0.9841 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.0983 - tp: 20171.0000 - fp: 1190.0000 - tn: 19269.0000 - fn: 330.0000 - accuracy: 0.9629 - precision: 0.9443 - recall: 0.9839 - auc: 0.9942 - prc: 0.9938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.0983 - tp: 23203.0000 - fp: 1367.0000 - tn: 22158.0000 - fn: 376.0000 - accuracy: 0.9630 - precision: 0.9444 - recall: 0.9841 - auc: 0.9942 - prc: 0.9938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.0975 - tp: 26260.0000 - fp: 1526.0000 - tn: 25043.0000 - fn: 419.0000 - accuracy: 0.9635 - precision: 0.9451 - recall: 0.9843 - auc: 0.9943 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.0971 - tp: 29246.0000 - fp: 1676.0000 - tn: 28000.0000 - fn: 470.0000 - accuracy: 0.9639 - precision: 0.9458 - recall: 0.9842 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.0978 - tp: 32302.0000 - fp: 1861.0000 - tn: 30860.0000 - fn: 513.0000 - accuracy: 0.9638 - precision: 0.9455 - recall: 0.9844 - auc: 0.9943 - prc: 0.9939"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/278 [==>...........................] - ETA: 5s - loss: 0.0973 - tp: 35364.0000 - fp: 2022.0000 - tn: 33730.0000 - fn: 564.0000 - accuracy: 0.9639 - precision: 0.9459 - recall: 0.9843 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/278 [===>..........................] - ETA: 5s - loss: 0.0971 - tp: 38471.0000 - fp: 2179.0000 - tn: 36559.0000 - fn: 615.0000 - accuracy: 0.9641 - precision: 0.9464 - recall: 0.9843 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 5s - loss: 0.0973 - tp: 41442.0000 - fp: 2373.0000 - tn: 39493.0000 - fn: 660.0000 - accuracy: 0.9639 - precision: 0.9458 - recall: 0.9843 - auc: 0.9943 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/278 [===>..........................] - ETA: 5s - loss: 0.0971 - tp: 44428.0000 - fp: 2545.0000 - tn: 42430.0000 - fn: 709.0000 - accuracy: 0.9639 - precision: 0.9458 - recall: 0.9843 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/278 [====>.........................] - ETA: 5s - loss: 0.0971 - tp: 47479.0000 - fp: 2720.0000 - tn: 45302.0000 - fn: 755.0000 - accuracy: 0.9639 - precision: 0.9458 - recall: 0.9843 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 4s - loss: 0.0969 - tp: 50412.0000 - fp: 2875.0000 - tn: 48309.0000 - fn: 804.0000 - accuracy: 0.9641 - precision: 0.9460 - recall: 0.9843 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.0968 - tp: 53382.0000 - fp: 3037.0000 - tn: 51279.0000 - fn: 846.0000 - accuracy: 0.9642 - precision: 0.9462 - recall: 0.9844 - auc: 0.9944 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.0970 - tp: 56406.0000 - fp: 3224.0000 - tn: 54167.0000 - fn: 891.0000 - accuracy: 0.9641 - precision: 0.9459 - recall: 0.9844 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.0967 - tp: 59391.0000 - fp: 3385.0000 - tn: 57115.0000 - fn: 941.0000 - accuracy: 0.9642 - precision: 0.9461 - recall: 0.9844 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.0966 - tp: 62435.0000 - fp: 3537.0000 - tn: 60012.0000 - fn: 992.0000 - accuracy: 0.9643 - precision: 0.9464 - recall: 0.9844 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.0963 - tp: 65454.0000 - fp: 3683.0000 - tn: 62947.0000 - fn: 1036.0000 - accuracy: 0.9646 - precision: 0.9467 - recall: 0.9844 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.0963 - tp: 68506.0000 - fp: 3855.0000 - tn: 65829.0000 - fn: 1074.0000 - accuracy: 0.9646 - precision: 0.9467 - recall: 0.9846 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.0963 - tp: 71484.0000 - fp: 4042.0000 - tn: 68765.0000 - fn: 1117.0000 - accuracy: 0.9645 - precision: 0.9465 - recall: 0.9846 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.0962 - tp: 74569.0000 - fp: 4199.0000 - tn: 71622.0000 - fn: 1162.0000 - accuracy: 0.9646 - precision: 0.9467 - recall: 0.9847 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.0962 - tp: 77533.0000 - fp: 4357.0000 - tn: 74598.0000 - fn: 1208.0000 - accuracy: 0.9647 - precision: 0.9468 - recall: 0.9847 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.0964 - tp: 80538.0000 - fp: 4536.0000 - tn: 77524.0000 - fn: 1242.0000 - accuracy: 0.9647 - precision: 0.9467 - recall: 0.9848 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.0962 - tp: 83563.0000 - fp: 4693.0000 - tn: 80449.0000 - fn: 1279.0000 - accuracy: 0.9649 - precision: 0.9468 - recall: 0.9849 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 4s - loss: 0.0961 - tp: 86607.0000 - fp: 4853.0000 - tn: 83346.0000 - fn: 1322.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9850 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 4s - loss: 0.0964 - tp: 89651.0000 - fp: 5042.0000 - tn: 86212.0000 - fn: 1367.0000 - accuracy: 0.9648 - precision: 0.9468 - recall: 0.9850 - auc: 0.9944 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 4s - loss: 0.0962 - tp: 92669.0000 - fp: 5200.0000 - tn: 89132.0000 - fn: 1415.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9850 - auc: 0.9945 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 4s - loss: 0.0962 - tp: 95722.0000 - fp: 5367.0000 - tn: 92011.0000 - fn: 1460.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9850 - auc: 0.9945 - prc: 0.9940"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.0962 - tp: 98690.0000 - fp: 5539.0000 - tn: 94966.0000 - fn: 1509.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9849 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.0962 - tp: 101746.0000 - fp: 5706.0000 - tn: 97835.0000 - fn: 1561.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9849 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 0.0963 - tp: 103760.0000 - fp: 5815.0000 - tn: 99775.0000 - fn: 1594.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9849 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.0960 - tp: 106801.0000 - fp: 5966.0000 - tn: 102691.0000 - fn: 1630.0000 - accuracy: 0.9650 - precision: 0.9471 - recall: 0.9850 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.0961 - tp: 109857.0000 - fp: 6154.0000 - tn: 105548.0000 - fn: 1673.0000 - accuracy: 0.9649 - precision: 0.9470 - recall: 0.9850 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.0961 - tp: 112879.0000 - fp: 6327.0000 - tn: 108455.0000 - fn: 1715.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9850 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.0962 - tp: 115866.0000 - fp: 6501.0000 - tn: 111392.0000 - fn: 1761.0000 - accuracy: 0.9649 - precision: 0.9469 - recall: 0.9850 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.0962 - tp: 118933.0000 - fp: 6665.0000 - tn: 114267.0000 - fn: 1799.0000 - accuracy: 0.9650 - precision: 0.9469 - recall: 0.9851 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.0962 - tp: 122045.0000 - fp: 6836.0000 - tn: 117085.0000 - fn: 1842.0000 - accuracy: 0.9650 - precision: 0.9470 - recall: 0.9851 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.0962 - tp: 125101.0000 - fp: 6996.0000 - tn: 119970.0000 - fn: 1885.0000 - accuracy: 0.9650 - precision: 0.9470 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.0961 - tp: 128082.0000 - fp: 7162.0000 - tn: 122923.0000 - fn: 1929.0000 - accuracy: 0.9650 - precision: 0.9470 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.0960 - tp: 131175.0000 - fp: 7342.0000 - tn: 125748.0000 - fn: 1975.0000 - accuracy: 0.9650 - precision: 0.9470 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.0960 - tp: 134170.0000 - fp: 7496.0000 - tn: 128702.0000 - fn: 2016.0000 - accuracy: 0.9651 - precision: 0.9471 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/278 [=============>................] - ETA: 3s - loss: 0.0960 - tp: 136198.0000 - fp: 7608.0000 - tn: 130623.0000 - fn: 2051.0000 - accuracy: 0.9651 - precision: 0.9471 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/278 [=============>................] - ETA: 3s - loss: 0.0959 - tp: 138211.0000 - fp: 7723.0000 - tn: 132561.0000 - fn: 2081.0000 - accuracy: 0.9651 - precision: 0.9471 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/278 [==============>...............] - ETA: 3s - loss: 0.0959 - tp: 140251.0000 - fp: 7831.0000 - tn: 134481.0000 - fn: 2109.0000 - accuracy: 0.9651 - precision: 0.9471 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/278 [==============>...............] - ETA: 3s - loss: 0.0958 - tp: 143228.0000 - fp: 7982.0000 - tn: 137449.0000 - fn: 2157.0000 - accuracy: 0.9651 - precision: 0.9472 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 2s - loss: 0.0958 - tp: 146258.0000 - fp: 8137.0000 - tn: 140368.0000 - fn: 2197.0000 - accuracy: 0.9652 - precision: 0.9473 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.0957 - tp: 149310.0000 - fp: 8308.0000 - tn: 143249.0000 - fn: 2237.0000 - accuracy: 0.9652 - precision: 0.9473 - recall: 0.9852 - auc: 0.9945 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.0958 - tp: 152380.0000 - fp: 8478.0000 - tn: 146102.0000 - fn: 2288.0000 - accuracy: 0.9652 - precision: 0.9473 - recall: 0.9852 - auc: 0.9945 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.0958 - tp: 155408.0000 - fp: 8669.0000 - tn: 148979.0000 - fn: 2336.0000 - accuracy: 0.9651 - precision: 0.9472 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.0958 - tp: 158423.0000 - fp: 8852.0000 - tn: 151883.0000 - fn: 2378.0000 - accuracy: 0.9651 - precision: 0.9471 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.0957 - tp: 161427.0000 - fp: 9004.0000 - tn: 154827.0000 - fn: 2422.0000 - accuracy: 0.9651 - precision: 0.9472 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.0957 - tp: 164390.0000 - fp: 9152.0000 - tn: 157816.0000 - fn: 2466.0000 - accuracy: 0.9652 - precision: 0.9473 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.0956 - tp: 167487.0000 - fp: 9309.0000 - tn: 160652.0000 - fn: 2520.0000 - accuracy: 0.9652 - precision: 0.9473 - recall: 0.9852 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.0956 - tp: 170479.0000 - fp: 9468.0000 - tn: 163603.0000 - fn: 2562.0000 - accuracy: 0.9652 - precision: 0.9474 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.0956 - tp: 173480.0000 - fp: 9638.0000 - tn: 166535.0000 - fn: 2603.0000 - accuracy: 0.9652 - precision: 0.9474 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.0955 - tp: 176490.0000 - fp: 9792.0000 - tn: 169475.0000 - fn: 2643.0000 - accuracy: 0.9653 - precision: 0.9474 - recall: 0.9852 - auc: 0.9945 - prc: 0.9941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.0954 - tp: 179486.0000 - fp: 9968.0000 - tn: 172408.0000 - fn: 2682.0000 - accuracy: 0.9653 - precision: 0.9474 - recall: 0.9853 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.0953 - tp: 182518.0000 - fp: 10122.0000 - tn: 175336.0000 - fn: 2712.0000 - accuracy: 0.9654 - precision: 0.9475 - recall: 0.9854 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/278 [==================>...........] - ETA: 2s - loss: 0.0952 - tp: 185508.0000 - fp: 10286.0000 - tn: 178277.0000 - fn: 2761.0000 - accuracy: 0.9654 - precision: 0.9475 - recall: 0.9853 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 2s - loss: 0.0953 - tp: 188477.0000 - fp: 10467.0000 - tn: 181228.0000 - fn: 2804.0000 - accuracy: 0.9653 - precision: 0.9474 - recall: 0.9853 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/278 [===================>..........] - ETA: 1s - loss: 0.0952 - tp: 191515.0000 - fp: 10638.0000 - tn: 184126.0000 - fn: 2841.0000 - accuracy: 0.9654 - precision: 0.9474 - recall: 0.9854 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.0951 - tp: 194509.0000 - fp: 10796.0000 - tn: 187080.0000 - fn: 2879.0000 - accuracy: 0.9654 - precision: 0.9474 - recall: 0.9854 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.0951 - tp: 197560.0000 - fp: 10957.0000 - tn: 189975.0000 - fn: 2916.0000 - accuracy: 0.9654 - precision: 0.9475 - recall: 0.9855 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.0951 - tp: 200603.0000 - fp: 11115.0000 - tn: 192878.0000 - fn: 2956.0000 - accuracy: 0.9655 - precision: 0.9475 - recall: 0.9855 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.0950 - tp: 203661.0000 - fp: 11285.0000 - tn: 195758.0000 - fn: 2992.0000 - accuracy: 0.9655 - precision: 0.9475 - recall: 0.9855 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.0950 - tp: 206721.0000 - fp: 11445.0000 - tn: 198636.0000 - fn: 3038.0000 - accuracy: 0.9655 - precision: 0.9475 - recall: 0.9855 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.0950 - tp: 209715.0000 - fp: 11615.0000 - tn: 201583.0000 - fn: 3071.0000 - accuracy: 0.9655 - precision: 0.9475 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.0949 - tp: 212760.0000 - fp: 11780.0000 - tn: 204476.0000 - fn: 3112.0000 - accuracy: 0.9655 - precision: 0.9475 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "214/278 [======================>.......] - ETA: 1s - loss: 0.0949 - tp: 215794.0000 - fp: 11939.0000 - tn: 207382.0000 - fn: 3157.0000 - accuracy: 0.9656 - precision: 0.9476 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "217/278 [======================>.......] - ETA: 1s - loss: 0.0949 - tp: 218855.0000 - fp: 12114.0000 - tn: 210252.0000 - fn: 3195.0000 - accuracy: 0.9656 - precision: 0.9476 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "220/278 [======================>.......] - ETA: 1s - loss: 0.0948 - tp: 221913.0000 - fp: 12267.0000 - tn: 213143.0000 - fn: 3237.0000 - accuracy: 0.9656 - precision: 0.9476 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.0948 - tp: 223916.0000 - fp: 12374.0000 - tn: 215101.0000 - fn: 3265.0000 - accuracy: 0.9656 - precision: 0.9476 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/278 [=======================>......] - ETA: 1s - loss: 0.0947 - tp: 226012.0000 - fp: 12466.0000 - tn: 216978.0000 - fn: 3296.0000 - accuracy: 0.9656 - precision: 0.9477 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "227/278 [=======================>......] - ETA: 1s - loss: 0.0947 - tp: 229074.0000 - fp: 12616.0000 - tn: 219869.0000 - fn: 3337.0000 - accuracy: 0.9657 - precision: 0.9478 - recall: 0.9856 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "230/278 [=======================>......] - ETA: 1s - loss: 0.0946 - tp: 232111.0000 - fp: 12789.0000 - tn: 222764.0000 - fn: 3376.0000 - accuracy: 0.9657 - precision: 0.9478 - recall: 0.9857 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/278 [========================>.....] - ETA: 1s - loss: 0.0946 - tp: 234099.0000 - fp: 12899.0000 - tn: 224739.0000 - fn: 3399.0000 - accuracy: 0.9657 - precision: 0.9478 - recall: 0.9857 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.0945 - tp: 237152.0000 - fp: 13065.0000 - tn: 227622.0000 - fn: 3441.0000 - accuracy: 0.9657 - precision: 0.9478 - recall: 0.9857 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.0946 - tp: 240171.0000 - fp: 13231.0000 - tn: 230546.0000 - fn: 3476.0000 - accuracy: 0.9657 - precision: 0.9478 - recall: 0.9857 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/278 [=========================>....] - ETA: 0s - loss: 0.0946 - tp: 243167.0000 - fp: 13412.0000 - tn: 233476.0000 - fn: 3513.0000 - accuracy: 0.9657 - precision: 0.9477 - recall: 0.9858 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.0946 - tp: 246269.0000 - fp: 13587.0000 - tn: 236301.0000 - fn: 3555.0000 - accuracy: 0.9657 - precision: 0.9477 - recall: 0.9858 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "247/278 [=========================>....] - ETA: 0s - loss: 0.0947 - tp: 249283.0000 - fp: 13776.0000 - tn: 239205.0000 - fn: 3592.0000 - accuracy: 0.9657 - precision: 0.9476 - recall: 0.9858 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/278 [=========================>....] - ETA: 0s - loss: 0.0947 - tp: 252260.0000 - fp: 13936.0000 - tn: 242174.0000 - fn: 3630.0000 - accuracy: 0.9657 - precision: 0.9476 - recall: 0.9858 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.0947 - tp: 254328.0000 - fp: 14049.0000 - tn: 244072.0000 - fn: 3647.0000 - accuracy: 0.9657 - precision: 0.9477 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.0947 - tp: 257386.0000 - fp: 14225.0000 - tn: 246940.0000 - fn: 3689.0000 - accuracy: 0.9657 - precision: 0.9476 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.0947 - tp: 260353.0000 - fp: 14399.0000 - tn: 249904.0000 - fn: 3728.0000 - accuracy: 0.9657 - precision: 0.9476 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.0946 - tp: 263360.0000 - fp: 14549.0000 - tn: 252860.0000 - fn: 3759.0000 - accuracy: 0.9657 - precision: 0.9476 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.0946 - tp: 266389.0000 - fp: 14706.0000 - tn: 255773.0000 - fn: 3804.0000 - accuracy: 0.9658 - precision: 0.9477 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.0946 - tp: 269373.0000 - fp: 14882.0000 - tn: 258719.0000 - fn: 3842.0000 - accuracy: 0.9658 - precision: 0.9476 - recall: 0.9859 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.0945 - tp: 272413.0000 - fp: 15035.0000 - tn: 261638.0000 - fn: 3874.0000 - accuracy: 0.9658 - precision: 0.9477 - recall: 0.9860 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.0945 - tp: 275476.0000 - fp: 15195.0000 - tn: 264529.0000 - fn: 3904.0000 - accuracy: 0.9658 - precision: 0.9477 - recall: 0.9860 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.0944 - tp: 278484.0000 - fp: 15374.0000 - tn: 267452.0000 - fn: 3938.0000 - accuracy: 0.9658 - precision: 0.9477 - recall: 0.9861 - auc: 0.9946 - prc: 0.9942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 2.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "278/278 [==============================] - 6s 23ms/step - loss: 0.0944 - tp: 280510.0000 - fp: 15490.0000 - tn: 269381.0000 - fn: 3963.0000 - accuracy: 0.9658 - precision: 0.9477 - recall: 0.9861 - auc: 0.9946 - prc: 0.9942 - val_loss: 0.0319 - val_tp: 65.0000 - val_fp: 576.0000 - val_tn: 44924.0000 - val_fn: 4.0000 - val_accuracy: 0.9873 - val_precision: 0.1014 - val_recall: 0.9420 - val_auc: 0.9869 - val_prc: 0.7762\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12: early stopping\n"
     ]
    }
   ],
   "source": [
    "resampled_model = make_model()\n",
    "resampled_model.load_weights(initial_weights)\n",
    "\n",
    "# Reset the bias to zero, since this dataset is balanced.\n",
    "output_layer = resampled_model.layers[-1] \n",
    "output_layer.bias.assign([0])\n",
    "\n",
    "val_ds = tf.data.Dataset.from_tensor_slices((val_features, val_labels)).cache()\n",
    "val_ds = val_ds.batch(BATCH_SIZE).prefetch(2) \n",
    "\n",
    "resampled_history = resampled_model.fit(\n",
    "    resampled_ds,\n",
    "    epochs=EPOCHS,\n",
    "    steps_per_epoch=resampled_steps_per_epoch,\n",
    "    callbacks = [early_stopping],\n",
    "    validation_data=val_ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "avALvzUp3T_c"
   },
   "source": [
    "如果训练过程在每次梯度更新时都考虑整个数据集，那么这种过采样将与类加权基本相同。\n",
    "\n",
    "但是，当按批次训练模型时（如您在上面所做的那样），过采样的数据将提供更加平滑的梯度信号：不在一个权重较大的批次中显示每个正样本，而是在许多具有较小权重的不同批次中分别显示。\n",
    "\n",
    "这种更平滑的梯度信号使训练模型变得更加容易。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "klHZ0HV76VC5"
   },
   "source": [
    "### 查看训练历史记录\n",
    "\n",
    "请注意，此处的指标分布将有所不同，因为训练数据与验证和测试数据的分布完全不同。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:18:55.966820Z",
     "iopub.status.busy": "2023-11-08T01:18:55.966049Z",
     "iopub.status.idle": "2023-11-08T01:18:56.681437Z",
     "shell.execute_reply": "2023-11-08T01:18:56.680644Z"
    },
    "id": "YoUGfr1vuivl"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_metrics(resampled_history )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1PuH3A2vnwrh"
   },
   "source": [
    "### 重新训练\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KFLxRL8eoDE5"
   },
   "source": [
    "由于在平衡数据上训练更加容易，上面的训练过程可能很快就会过拟合。\n",
    "\n",
    "因此，请打破周期，使 `callbacks.EarlyStopping` 能够更好地控制停止训练的时间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:18:56.686046Z",
     "iopub.status.busy": "2023-11-08T01:18:56.685753Z",
     "iopub.status.idle": "2023-11-08T01:19:17.970739Z",
     "shell.execute_reply": "2023-11-08T01:19:17.969849Z"
    },
    "id": "e_yn9I26qAHU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 31s - loss: 2.3586 - tp: 341.0000 - fp: 708.0000 - tn: 45796.0000 - fn: 772.0000 - accuracy: 0.9689 - precision: 0.3251 - recall: 0.3064 - auc: 0.8042 - prc: 0.3184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 2.1916 - tp: 1567.0000 - fp: 1317.0000 - tn: 49299.0000 - fn: 3626.0000 - accuracy: 0.9114 - precision: 0.5433 - recall: 0.3018 - auc: 0.7706 - prc: 0.4349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 2.1376 - tp: 2222.0000 - fp: 1639.0000 - tn: 51053.0000 - fn: 4991.0000 - accuracy: 0.8893 - precision: 0.5755 - recall: 0.3081 - auc: 0.7610 - prc: 0.4634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 9/20 [============>.................] - ETA: 0s - loss: 2.0971 - tp: 2895.0000 - fp: 1953.0000 - tn: 52764.0000 - fn: 6389.0000 - accuracy: 0.8697 - precision: 0.5972 - recall: 0.3118 - auc: 0.7521 - prc: 0.4866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 2.0694 - tp: 3605.0000 - fp: 2249.0000 - tn: 54476.0000 - fn: 7767.0000 - accuracy: 0.8529 - precision: 0.6158 - recall: 0.3170 - auc: 0.7433 - prc: 0.5047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 2.0243 - tp: 4348.0000 - fp: 2523.0000 - tn: 56248.0000 - fn: 9074.0000 - accuracy: 0.8394 - precision: 0.6328 - recall: 0.3239 - auc: 0.7366 - prc: 0.5222"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 1.9660 - tp: 5503.0000 - fp: 3027.0000 - tn: 58763.0000 - fn: 11044.0000 - accuracy: 0.8204 - precision: 0.6451 - recall: 0.3326 - auc: 0.7283 - prc: 0.5430"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 1.9021 - tp: 6740.0000 - fp: 3546.0000 - tn: 61316.0000 - fn: 12879.0000 - accuracy: 0.8056 - precision: 0.6553 - recall: 0.3435 - auc: 0.7222 - prc: 0.5611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 3s 55ms/step - loss: 1.8818 - tp: 7147.0000 - fp: 3701.0000 - tn: 62207.0000 - fn: 13474.0000 - accuracy: 0.8015 - precision: 0.6588 - recall: 0.3466 - auc: 0.7204 - prc: 0.5663 - val_loss: 0.3562 - val_tp: 18.0000 - val_fp: 3378.0000 - val_tn: 42122.0000 - val_fn: 51.0000 - val_accuracy: 0.9248 - val_precision: 0.0053 - val_recall: 0.2609 - val_auc: 0.5310 - val_prc: 0.0789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 1.5262 - tp: 445.0000 - fp: 180.0000 - tn: 809.0000 - fn: 614.0000 - accuracy: 0.6123 - precision: 0.7120 - recall: 0.4202 - auc: 0.5283 - prc: 0.6932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 1.4618 - tp: 1772.0000 - fp: 706.0000 - tn: 3282.0000 - fn: 2432.0000 - accuracy: 0.6169 - precision: 0.7151 - recall: 0.4215 - auc: 0.5330 - prc: 0.6927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 1.4372 - tp: 2669.0000 - fp: 1085.0000 - tn: 4942.0000 - fn: 3592.0000 - accuracy: 0.6194 - precision: 0.7110 - recall: 0.4263 - auc: 0.5334 - prc: 0.6912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 1.4016 - tp: 3601.0000 - fp: 1466.0000 - tn: 6609.0000 - fn: 4708.0000 - accuracy: 0.6232 - precision: 0.7107 - recall: 0.4334 - auc: 0.5400 - prc: 0.6946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 1.3723 - tp: 4513.0000 - fp: 1849.0000 - tn: 8315.0000 - fn: 5803.0000 - accuracy: 0.6264 - precision: 0.7094 - recall: 0.4375 - auc: 0.5436 - prc: 0.6949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 1.3289 - tp: 5924.0000 - fp: 2443.0000 - tn: 10886.0000 - fn: 7371.0000 - accuracy: 0.6314 - precision: 0.7080 - recall: 0.4456 - auc: 0.5509 - prc: 0.6976"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 1.2865 - tp: 7414.0000 - fp: 2992.0000 - tn: 13380.0000 - fn: 8982.0000 - accuracy: 0.6346 - precision: 0.7125 - recall: 0.4522 - auc: 0.5588 - prc: 0.7034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 1.2579 - tp: 8953.0000 - fp: 3566.0000 - tn: 15839.0000 - fn: 10554.0000 - accuracy: 0.6371 - precision: 0.7152 - recall: 0.4590 - auc: 0.5649 - prc: 0.7085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 1.2506 - tp: 9432.0000 - fp: 3742.0000 - tn: 16690.0000 - fn: 11096.0000 - accuracy: 0.6377 - precision: 0.7160 - recall: 0.4595 - auc: 0.5656 - prc: 0.7088 - val_loss: 0.3813 - val_tp: 46.0000 - val_fp: 4274.0000 - val_tn: 41226.0000 - val_fn: 23.0000 - val_accuracy: 0.9057 - val_precision: 0.0106 - val_recall: 0.6667 - val_auc: 0.7818 - val_prc: 0.3564\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 1.0355 - tp: 530.0000 - fp: 195.0000 - tn: 801.0000 - fn: 522.0000 - accuracy: 0.6499 - precision: 0.7310 - recall: 0.5038 - auc: 0.6139 - prc: 0.7476"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 1.0138 - tp: 2066.0000 - fp: 794.0000 - tn: 3346.0000 - fn: 1986.0000 - accuracy: 0.6606 - precision: 0.7224 - recall: 0.5099 - auc: 0.6141 - prc: 0.7373"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 1.0074 - tp: 3132.0000 - fp: 1231.0000 - tn: 4929.0000 - fn: 2996.0000 - accuracy: 0.6560 - precision: 0.7179 - recall: 0.5111 - auc: 0.6157 - prc: 0.7400"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.9885 - tp: 4241.0000 - fp: 1665.0000 - tn: 6559.0000 - fn: 3919.0000 - accuracy: 0.6592 - precision: 0.7181 - recall: 0.5197 - auc: 0.6236 - prc: 0.7452"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.9672 - tp: 5879.0000 - fp: 2267.0000 - tn: 9036.0000 - fn: 5346.0000 - accuracy: 0.6621 - precision: 0.7217 - recall: 0.5237 - auc: 0.6285 - prc: 0.7485"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.9441 - tp: 7588.0000 - fp: 2900.0000 - tn: 11465.0000 - fn: 6719.0000 - accuracy: 0.6645 - precision: 0.7235 - recall: 0.5304 - auc: 0.6352 - prc: 0.7532"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.9242 - tp: 9335.0000 - fp: 3551.0000 - tn: 13895.0000 - fn: 8035.0000 - accuracy: 0.6672 - precision: 0.7244 - recall: 0.5374 - auc: 0.6415 - prc: 0.7574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.9031 - tp: 11130.0000 - fp: 4216.0000 - tn: 16301.0000 - fn: 9313.0000 - accuracy: 0.6697 - precision: 0.7253 - recall: 0.5444 - auc: 0.6484 - prc: 0.7620"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.9031 - tp: 11130.0000 - fp: 4216.0000 - tn: 16301.0000 - fn: 9313.0000 - accuracy: 0.6697 - precision: 0.7253 - recall: 0.5444 - auc: 0.6484 - prc: 0.7620 - val_loss: 0.3923 - val_tp: 57.0000 - val_fp: 4628.0000 - val_tn: 40872.0000 - val_fn: 12.0000 - val_accuracy: 0.8982 - val_precision: 0.0122 - val_recall: 0.8261 - val_auc: 0.9040 - val_prc: 0.5297\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.7573 - tp: 637.0000 - fp: 209.0000 - tn: 790.0000 - fn: 412.0000 - accuracy: 0.6968 - precision: 0.7530 - recall: 0.6072 - auc: 0.7049 - prc: 0.8056"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.7445 - tp: 3115.0000 - fp: 1020.0000 - tn: 4064.0000 - fn: 2041.0000 - accuracy: 0.7011 - precision: 0.7533 - recall: 0.6042 - auc: 0.7050 - prc: 0.8005"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.7328 - tp: 5005.0000 - fp: 1648.0000 - tn: 6510.0000 - fn: 3221.0000 - accuracy: 0.7028 - precision: 0.7523 - recall: 0.6084 - auc: 0.7110 - prc: 0.8035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.7137 - tp: 6910.0000 - fp: 2229.0000 - tn: 9033.0000 - fn: 4356.0000 - accuracy: 0.7077 - precision: 0.7561 - recall: 0.6133 - auc: 0.7184 - prc: 0.8074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.7012 - tp: 8899.0000 - fp: 2817.0000 - tn: 11509.0000 - fn: 5447.0000 - accuracy: 0.7118 - precision: 0.7596 - recall: 0.6203 - auc: 0.7250 - prc: 0.8118"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.6929 - tp: 10919.0000 - fp: 3416.0000 - tn: 13997.0000 - fn: 6484.0000 - accuracy: 0.7156 - precision: 0.7617 - recall: 0.6274 - auc: 0.7298 - prc: 0.8151"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.6819 - tp: 12966.0000 - fp: 4063.0000 - tn: 16442.0000 - fn: 7489.0000 - accuracy: 0.7180 - precision: 0.7614 - recall: 0.6339 - auc: 0.7355 - prc: 0.8188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.6819 - tp: 12966.0000 - fp: 4063.0000 - tn: 16442.0000 - fn: 7489.0000 - accuracy: 0.7180 - precision: 0.7614 - recall: 0.6339 - auc: 0.7355 - prc: 0.8188 - val_loss: 0.3901 - val_tp: 60.0000 - val_fp: 4341.0000 - val_tn: 41159.0000 - val_fn: 9.0000 - val_accuracy: 0.9045 - val_precision: 0.0136 - val_recall: 0.8696 - val_auc: 0.9306 - val_prc: 0.6600\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.6302 - tp: 687.0000 - fp: 213.0000 - tn: 807.0000 - fn: 341.0000 - accuracy: 0.7295 - precision: 0.7633 - recall: 0.6683 - auc: 0.7665 - prc: 0.8408"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.5897 - tp: 3488.0000 - fp: 1042.0000 - tn: 4098.0000 - fn: 1612.0000 - accuracy: 0.7408 - precision: 0.7700 - recall: 0.6839 - auc: 0.7850 - prc: 0.8518"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.5875 - tp: 5618.0000 - fp: 1629.0000 - tn: 6582.0000 - fn: 2555.0000 - accuracy: 0.7446 - precision: 0.7752 - recall: 0.6874 - auc: 0.7848 - prc: 0.8518"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.5868 - tp: 7759.0000 - fp: 2242.0000 - tn: 9032.0000 - fn: 3495.0000 - accuracy: 0.7453 - precision: 0.7758 - recall: 0.6894 - auc: 0.7855 - prc: 0.8525"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.5794 - tp: 9903.0000 - fp: 2850.0000 - tn: 11516.0000 - fn: 4403.0000 - accuracy: 0.7470 - precision: 0.7765 - recall: 0.6922 - auc: 0.7882 - prc: 0.8540"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.5682 - tp: 12110.0000 - fp: 3460.0000 - tn: 14012.0000 - fn: 5234.0000 - accuracy: 0.7503 - precision: 0.7778 - recall: 0.6982 - auc: 0.7936 - prc: 0.8572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.5618 - tp: 14319.0000 - fp: 4049.0000 - tn: 16518.0000 - fn: 6074.0000 - accuracy: 0.7529 - precision: 0.7796 - recall: 0.7022 - auc: 0.7971 - prc: 0.8594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.5618 - tp: 14319.0000 - fp: 4049.0000 - tn: 16518.0000 - fn: 6074.0000 - accuracy: 0.7529 - precision: 0.7796 - recall: 0.7022 - auc: 0.7971 - prc: 0.8594 - val_loss: 0.3759 - val_tp: 62.0000 - val_fp: 3600.0000 - val_tn: 41900.0000 - val_fn: 7.0000 - val_accuracy: 0.9208 - val_precision: 0.0169 - val_recall: 0.8986 - val_auc: 0.9432 - val_prc: 0.6929\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.5119 - tp: 749.0000 - fp: 189.0000 - tn: 837.0000 - fn: 273.0000 - accuracy: 0.7744 - precision: 0.7985 - recall: 0.7329 - auc: 0.8254 - prc: 0.8804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.5119 - tp: 3775.0000 - fp: 974.0000 - tn: 4161.0000 - fn: 1330.0000 - accuracy: 0.7750 - precision: 0.7949 - recall: 0.7395 - auc: 0.8266 - prc: 0.8798"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.5041 - tp: 6076.0000 - fp: 1503.0000 - tn: 6639.0000 - fn: 2166.0000 - accuracy: 0.7761 - precision: 0.8017 - recall: 0.7372 - auc: 0.8287 - prc: 0.8823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.5025 - tp: 8391.0000 - fp: 2080.0000 - tn: 9103.0000 - fn: 2954.0000 - accuracy: 0.7765 - precision: 0.8014 - recall: 0.7396 - auc: 0.8304 - prc: 0.8836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.4961 - tp: 10709.0000 - fp: 2614.0000 - tn: 11634.0000 - fn: 3715.0000 - accuracy: 0.7793 - precision: 0.8038 - recall: 0.7424 - auc: 0.8340 - prc: 0.8854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.4922 - tp: 13021.0000 - fp: 3153.0000 - tn: 14164.0000 - fn: 4478.0000 - accuracy: 0.7808 - precision: 0.8051 - recall: 0.7441 - auc: 0.8361 - prc: 0.8866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.4880 - tp: 15347.0000 - fp: 3721.0000 - tn: 16696.0000 - fn: 5196.0000 - accuracy: 0.7823 - precision: 0.8049 - recall: 0.7471 - auc: 0.8385 - prc: 0.8877"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.4880 - tp: 15347.0000 - fp: 3721.0000 - tn: 16696.0000 - fn: 5196.0000 - accuracy: 0.7823 - precision: 0.8049 - recall: 0.7471 - auc: 0.8385 - prc: 0.8877 - val_loss: 0.3542 - val_tp: 63.0000 - val_fp: 2857.0000 - val_tn: 42643.0000 - val_fn: 6.0000 - val_accuracy: 0.9372 - val_precision: 0.0216 - val_recall: 0.9130 - val_auc: 0.9539 - val_prc: 0.7195\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4561 - tp: 785.0000 - fp: 152.0000 - tn: 857.0000 - fn: 254.0000 - accuracy: 0.8018 - precision: 0.8378 - recall: 0.7555 - auc: 0.8514 - prc: 0.8983"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.4588 - tp: 3931.0000 - fp: 835.0000 - tn: 4242.0000 - fn: 1232.0000 - accuracy: 0.7981 - precision: 0.8248 - recall: 0.7614 - auc: 0.8551 - prc: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.4549 - tp: 6283.0000 - fp: 1358.0000 - tn: 6804.0000 - fn: 1939.0000 - accuracy: 0.7988 - precision: 0.8223 - recall: 0.7642 - auc: 0.8570 - prc: 0.9002"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.4541 - tp: 8659.0000 - fp: 1842.0000 - tn: 9380.0000 - fn: 2647.0000 - accuracy: 0.8007 - precision: 0.8246 - recall: 0.7659 - auc: 0.8577 - prc: 0.9011"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.4522 - tp: 11020.0000 - fp: 2348.0000 - tn: 11937.0000 - fn: 3367.0000 - accuracy: 0.8007 - precision: 0.8244 - recall: 0.7660 - auc: 0.8587 - prc: 0.9016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.4501 - tp: 13360.0000 - fp: 2823.0000 - tn: 14559.0000 - fn: 4074.0000 - accuracy: 0.8019 - precision: 0.8256 - recall: 0.7663 - auc: 0.8596 - prc: 0.9020"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.4461 - tp: 15816.0000 - fp: 3280.0000 - tn: 17103.0000 - fn: 4761.0000 - accuracy: 0.8037 - precision: 0.8282 - recall: 0.7686 - auc: 0.8619 - prc: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.4461 - tp: 15816.0000 - fp: 3280.0000 - tn: 17103.0000 - fn: 4761.0000 - accuracy: 0.8037 - precision: 0.8282 - recall: 0.7686 - auc: 0.8619 - prc: 0.9038 - val_loss: 0.3301 - val_tp: 64.0000 - val_fp: 2195.0000 - val_tn: 43305.0000 - val_fn: 5.0000 - val_accuracy: 0.9517 - val_precision: 0.0283 - val_recall: 0.9275 - val_auc: 0.9639 - val_prc: 0.7314\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4614 - tp: 755.0000 - fp: 173.0000 - tn: 863.0000 - fn: 257.0000 - accuracy: 0.7900 - precision: 0.8136 - recall: 0.7460 - auc: 0.8549 - prc: 0.8971"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.4361 - tp: 3881.0000 - fp: 817.0000 - tn: 4379.0000 - fn: 1163.0000 - accuracy: 0.8066 - precision: 0.8261 - recall: 0.7694 - auc: 0.8664 - prc: 0.9044"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.4357 - tp: 6221.0000 - fp: 1293.0000 - tn: 7007.0000 - fn: 1863.0000 - accuracy: 0.8074 - precision: 0.8279 - recall: 0.7695 - auc: 0.8668 - prc: 0.9051"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.4325 - tp: 8606.0000 - fp: 1706.0000 - tn: 9679.0000 - fn: 2537.0000 - accuracy: 0.8117 - precision: 0.8346 - recall: 0.7723 - auc: 0.8690 - prc: 0.9068"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.4273 - tp: 11064.0000 - fp: 2103.0000 - tn: 12286.0000 - fn: 3219.0000 - accuracy: 0.8144 - precision: 0.8403 - recall: 0.7746 - auc: 0.8722 - prc: 0.9095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.4216 - tp: 13496.0000 - fp: 2483.0000 - tn: 14975.0000 - fn: 3862.0000 - accuracy: 0.8178 - precision: 0.8446 - recall: 0.7775 - auc: 0.8751 - prc: 0.9116"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.4191 - tp: 15893.0000 - fp: 2891.0000 - tn: 17619.0000 - fn: 4557.0000 - accuracy: 0.8182 - precision: 0.8461 - recall: 0.7772 - auc: 0.8764 - prc: 0.9124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.4191 - tp: 15893.0000 - fp: 2891.0000 - tn: 17619.0000 - fn: 4557.0000 - accuracy: 0.8182 - precision: 0.8461 - recall: 0.7772 - auc: 0.8764 - prc: 0.9124 - val_loss: 0.3054 - val_tp: 64.0000 - val_fp: 1742.0000 - val_tn: 43758.0000 - val_fn: 5.0000 - val_accuracy: 0.9617 - val_precision: 0.0354 - val_recall: 0.9275 - val_auc: 0.9734 - val_prc: 0.7366\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4088 - tp: 835.0000 - fp: 133.0000 - tn: 861.0000 - fn: 219.0000 - accuracy: 0.8281 - precision: 0.8626 - recall: 0.7922 - auc: 0.8840 - prc: 0.9223"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.3971 - tp: 3988.0000 - fp: 675.0000 - tn: 4491.0000 - fn: 1086.0000 - accuracy: 0.8280 - precision: 0.8552 - recall: 0.7860 - auc: 0.8874 - prc: 0.9185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3954 - tp: 6376.0000 - fp: 1066.0000 - tn: 7199.0000 - fn: 1743.0000 - accuracy: 0.8286 - precision: 0.8568 - recall: 0.7853 - auc: 0.8890 - prc: 0.9193"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.3918 - tp: 8842.0000 - fp: 1488.0000 - tn: 9834.0000 - fn: 2364.0000 - accuracy: 0.8290 - precision: 0.8560 - recall: 0.7890 - auc: 0.8912 - prc: 0.9210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3918 - tp: 11238.0000 - fp: 1836.0000 - tn: 12579.0000 - fn: 3019.0000 - accuracy: 0.8307 - precision: 0.8596 - recall: 0.7882 - auc: 0.8916 - prc: 0.9210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3918 - tp: 13668.0000 - fp: 2201.0000 - tn: 15257.0000 - fn: 3690.0000 - accuracy: 0.8308 - precision: 0.8613 - recall: 0.7874 - auc: 0.8916 - prc: 0.9211"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.3895 - tp: 16135.0000 - fp: 2567.0000 - tn: 17914.0000 - fn: 4344.0000 - accuracy: 0.8313 - precision: 0.8627 - recall: 0.7879 - auc: 0.8927 - prc: 0.9221"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.3895 - tp: 16135.0000 - fp: 2567.0000 - tn: 17914.0000 - fn: 4344.0000 - accuracy: 0.8313 - precision: 0.8627 - recall: 0.7879 - auc: 0.8927 - prc: 0.9221 - val_loss: 0.2812 - val_tp: 63.0000 - val_fp: 1410.0000 - val_tn: 44090.0000 - val_fn: 6.0000 - val_accuracy: 0.9689 - val_precision: 0.0428 - val_recall: 0.9130 - val_auc: 0.9811 - val_prc: 0.7399\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4063 - tp: 819.0000 - fp: 135.0000 - tn: 858.0000 - fn: 236.0000 - accuracy: 0.8188 - precision: 0.8585 - recall: 0.7763 - auc: 0.8828 - prc: 0.9192"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.3802 - tp: 4036.0000 - fp: 597.0000 - tn: 4495.0000 - fn: 1112.0000 - accuracy: 0.8331 - precision: 0.8711 - recall: 0.7840 - auc: 0.8960 - prc: 0.9253"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3776 - tp: 6489.0000 - fp: 987.0000 - tn: 7188.0000 - fn: 1720.0000 - accuracy: 0.8348 - precision: 0.8680 - recall: 0.7905 - auc: 0.8977 - prc: 0.9261"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.3750 - tp: 8943.0000 - fp: 1324.0000 - tn: 9922.0000 - fn: 2339.0000 - accuracy: 0.8374 - precision: 0.8710 - recall: 0.7927 - auc: 0.8997 - prc: 0.9273"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3747 - tp: 11397.0000 - fp: 1682.0000 - tn: 12610.0000 - fn: 2983.0000 - accuracy: 0.8373 - precision: 0.8714 - recall: 0.7926 - auc: 0.8998 - prc: 0.9276"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3739 - tp: 13906.0000 - fp: 2040.0000 - tn: 15270.0000 - fn: 3600.0000 - accuracy: 0.8380 - precision: 0.8721 - recall: 0.7944 - auc: 0.9005 - prc: 0.9283"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.3720 - tp: 16397.0000 - fp: 2348.0000 - tn: 18019.0000 - fn: 4196.0000 - accuracy: 0.8402 - precision: 0.8747 - recall: 0.7962 - auc: 0.9013 - prc: 0.9290"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.3720 - tp: 16397.0000 - fp: 2348.0000 - tn: 18019.0000 - fn: 4196.0000 - accuracy: 0.8402 - precision: 0.8747 - recall: 0.7962 - auc: 0.9013 - prc: 0.9290 - val_loss: 0.2592 - val_tp: 62.0000 - val_fp: 1199.0000 - val_tn: 44301.0000 - val_fn: 7.0000 - val_accuracy: 0.9735 - val_precision: 0.0492 - val_recall: 0.8986 - val_auc: 0.9869 - val_prc: 0.7455\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3565 - tp: 822.0000 - fp: 109.0000 - tn: 922.0000 - fn: 195.0000 - accuracy: 0.8516 - precision: 0.8829 - recall: 0.8083 - auc: 0.9076 - prc: 0.9331"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.3532 - tp: 4083.0000 - fp: 516.0000 - tn: 4678.0000 - fn: 963.0000 - accuracy: 0.8556 - precision: 0.8878 - recall: 0.8092 - auc: 0.9119 - prc: 0.9347"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3506 - tp: 6564.0000 - fp: 803.0000 - tn: 7464.0000 - fn: 1553.0000 - accuracy: 0.8562 - precision: 0.8910 - recall: 0.8087 - auc: 0.9122 - prc: 0.9356"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.3488 - tp: 9037.0000 - fp: 1107.0000 - tn: 10240.0000 - fn: 2144.0000 - accuracy: 0.8557 - precision: 0.8909 - recall: 0.8082 - auc: 0.9128 - prc: 0.9360"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3472 - tp: 11516.0000 - fp: 1383.0000 - tn: 13024.0000 - fn: 2749.0000 - accuracy: 0.8559 - precision: 0.8928 - recall: 0.8073 - auc: 0.9136 - prc: 0.9366"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3464 - tp: 14025.0000 - fp: 1682.0000 - tn: 15777.0000 - fn: 3332.0000 - accuracy: 0.8560 - precision: 0.8929 - recall: 0.8080 - auc: 0.9140 - prc: 0.9368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.3445 - tp: 16567.0000 - fp: 1952.0000 - tn: 18519.0000 - fn: 3922.0000 - accuracy: 0.8566 - precision: 0.8946 - recall: 0.8086 - auc: 0.9149 - prc: 0.9377"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.3445 - tp: 16567.0000 - fp: 1952.0000 - tn: 18519.0000 - fn: 3922.0000 - accuracy: 0.8566 - precision: 0.8946 - recall: 0.8086 - auc: 0.9149 - prc: 0.9377 - val_loss: 0.2394 - val_tp: 62.0000 - val_fp: 1050.0000 - val_tn: 44450.0000 - val_fn: 7.0000 - val_accuracy: 0.9768 - val_precision: 0.0558 - val_recall: 0.8986 - val_auc: 0.9902 - val_prc: 0.7474\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3318 - tp: 809.0000 - fp: 88.0000 - tn: 956.0000 - fn: 195.0000 - accuracy: 0.8618 - precision: 0.9019 - recall: 0.8058 - auc: 0.9202 - prc: 0.9406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.3348 - tp: 4121.0000 - fp: 458.0000 - tn: 4615.0000 - fn: 1046.0000 - accuracy: 0.8531 - precision: 0.9000 - recall: 0.7976 - auc: 0.9195 - prc: 0.9413"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3350 - tp: 6493.0000 - fp: 694.0000 - tn: 7437.0000 - fn: 1760.0000 - accuracy: 0.8502 - precision: 0.9034 - recall: 0.7867 - auc: 0.9194 - prc: 0.9410"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.3336 - tp: 8829.0000 - fp: 953.0000 - tn: 10294.0000 - fn: 2452.0000 - accuracy: 0.8489 - precision: 0.9026 - recall: 0.7826 - auc: 0.9202 - prc: 0.9407"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3327 - tp: 11259.0000 - fp: 1183.0000 - tn: 13071.0000 - fn: 3159.0000 - accuracy: 0.8486 - precision: 0.9049 - recall: 0.7809 - auc: 0.9208 - prc: 0.9414"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3314 - tp: 13617.0000 - fp: 1434.0000 - tn: 15903.0000 - fn: 3862.0000 - accuracy: 0.8479 - precision: 0.9047 - recall: 0.7790 - auc: 0.9214 - prc: 0.9417"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.3299 - tp: 16021.0000 - fp: 1682.0000 - tn: 18721.0000 - fn: 4536.0000 - accuracy: 0.8482 - precision: 0.9050 - recall: 0.7793 - auc: 0.9221 - prc: 0.9422"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.3299 - tp: 16021.0000 - fp: 1682.0000 - tn: 18721.0000 - fn: 4536.0000 - accuracy: 0.8482 - precision: 0.9050 - recall: 0.7793 - auc: 0.9221 - prc: 0.9422 - val_loss: 0.2220 - val_tp: 62.0000 - val_fp: 946.0000 - val_tn: 44554.0000 - val_fn: 7.0000 - val_accuracy: 0.9791 - val_precision: 0.0615 - val_recall: 0.8986 - val_auc: 0.9922 - val_prc: 0.7511\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3285 - tp: 812.0000 - fp: 70.0000 - tn: 919.0000 - fn: 247.0000 - accuracy: 0.8452 - precision: 0.9206 - recall: 0.7668 - auc: 0.9228 - prc: 0.9458"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.3249 - tp: 3177.0000 - fp: 309.0000 - tn: 3717.0000 - fn: 989.0000 - accuracy: 0.8416 - precision: 0.9114 - recall: 0.7626 - auc: 0.9250 - prc: 0.9446"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.3233 - tp: 4720.0000 - fp: 468.0000 - tn: 5640.0000 - fn: 1460.0000 - accuracy: 0.8431 - precision: 0.9098 - recall: 0.7638 - auc: 0.9255 - prc: 0.9440"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3199 - tp: 6346.0000 - fp: 621.0000 - tn: 7482.0000 - fn: 1935.0000 - accuracy: 0.8440 - precision: 0.9109 - recall: 0.7663 - auc: 0.9272 - prc: 0.9453"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.3186 - tp: 7965.0000 - fp: 774.0000 - tn: 9378.0000 - fn: 2363.0000 - accuracy: 0.8468 - precision: 0.9114 - recall: 0.7712 - auc: 0.9274 - prc: 0.9457"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.3157 - tp: 9579.0000 - fp: 909.0000 - tn: 11285.0000 - fn: 2803.0000 - accuracy: 0.8490 - precision: 0.9133 - recall: 0.7736 - auc: 0.9287 - prc: 0.9467"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3157 - tp: 11205.0000 - fp: 1058.0000 - tn: 13180.0000 - fn: 3229.0000 - accuracy: 0.8505 - precision: 0.9137 - recall: 0.7763 - auc: 0.9292 - prc: 0.9470"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3135 - tp: 13558.0000 - fp: 1272.0000 - tn: 16112.0000 - fn: 3874.0000 - accuracy: 0.8522 - precision: 0.9142 - recall: 0.7778 - auc: 0.9300 - prc: 0.9471"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.3143 - tp: 15899.0000 - fp: 1497.0000 - tn: 19005.0000 - fn: 4559.0000 - accuracy: 0.8521 - precision: 0.9139 - recall: 0.7772 - auc: 0.9297 - prc: 0.9467"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 32ms/step - loss: 0.3143 - tp: 15899.0000 - fp: 1497.0000 - tn: 19005.0000 - fn: 4559.0000 - accuracy: 0.8521 - precision: 0.9139 - recall: 0.7772 - auc: 0.9297 - prc: 0.9467 - val_loss: 0.2055 - val_tp: 62.0000 - val_fp: 882.0000 - val_tn: 44618.0000 - val_fn: 7.0000 - val_accuracy: 0.9805 - val_precision: 0.0657 - val_recall: 0.8986 - val_auc: 0.9934 - val_prc: 0.7536\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3191 - tp: 778.0000 - fp: 67.0000 - tn: 967.0000 - fn: 236.0000 - accuracy: 0.8521 - precision: 0.9207 - recall: 0.7673 - auc: 0.9250 - prc: 0.9441"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.3084 - tp: 3997.0000 - fp: 362.0000 - tn: 4714.0000 - fn: 1167.0000 - accuracy: 0.8507 - precision: 0.9170 - recall: 0.7740 - auc: 0.9315 - prc: 0.9487"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3104 - tp: 6402.0000 - fp: 579.0000 - tn: 7544.0000 - fn: 1859.0000 - accuracy: 0.8512 - precision: 0.9171 - recall: 0.7750 - auc: 0.9306 - prc: 0.9480"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.3088 - tp: 8002.0000 - fp: 711.0000 - tn: 9481.0000 - fn: 2286.0000 - accuracy: 0.8537 - precision: 0.9184 - recall: 0.7778 - auc: 0.9317 - prc: 0.9484"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.3079 - tp: 10409.0000 - fp: 917.0000 - tn: 12302.0000 - fn: 2996.0000 - accuracy: 0.8530 - precision: 0.9190 - recall: 0.7765 - auc: 0.9322 - prc: 0.9489"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.3091 - tp: 12762.0000 - fp: 1144.0000 - tn: 15191.0000 - fn: 3671.0000 - accuracy: 0.8531 - precision: 0.9177 - recall: 0.7766 - auc: 0.9319 - prc: 0.9484"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.3089 - tp: 15183.0000 - fp: 1377.0000 - tn: 17994.0000 - fn: 4358.0000 - accuracy: 0.8526 - precision: 0.9168 - recall: 0.7770 - auc: 0.9325 - prc: 0.9487"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.3082 - tp: 15953.0000 - fp: 1450.0000 - tn: 18984.0000 - fn: 4573.0000 - accuracy: 0.8530 - precision: 0.9167 - recall: 0.7772 - auc: 0.9327 - prc: 0.9487 - val_loss: 0.1903 - val_tp: 63.0000 - val_fp: 806.0000 - val_tn: 44694.0000 - val_fn: 6.0000 - val_accuracy: 0.9822 - val_precision: 0.0725 - val_recall: 0.9130 - val_auc: 0.9942 - val_prc: 0.7563\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2996 - tp: 820.0000 - fp: 67.0000 - tn: 931.0000 - fn: 230.0000 - accuracy: 0.8550 - precision: 0.9245 - recall: 0.7810 - auc: 0.9341 - prc: 0.9525"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2965 - tp: 3976.0000 - fp: 316.0000 - tn: 4802.0000 - fn: 1146.0000 - accuracy: 0.8572 - precision: 0.9264 - recall: 0.7763 - auc: 0.9368 - prc: 0.9517"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2971 - tp: 6327.0000 - fp: 529.0000 - tn: 7673.0000 - fn: 1855.0000 - accuracy: 0.8545 - precision: 0.9228 - recall: 0.7733 - auc: 0.9366 - prc: 0.9510"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2973 - tp: 8724.0000 - fp: 706.0000 - tn: 10544.0000 - fn: 2554.0000 - accuracy: 0.8553 - precision: 0.9251 - recall: 0.7735 - auc: 0.9368 - prc: 0.9514"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2970 - tp: 11143.0000 - fp: 898.0000 - tn: 13402.0000 - fn: 3229.0000 - accuracy: 0.8561 - precision: 0.9254 - recall: 0.7753 - auc: 0.9372 - prc: 0.9518"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2968 - tp: 13571.0000 - fp: 1094.0000 - tn: 16234.0000 - fn: 3917.0000 - accuracy: 0.8561 - precision: 0.9254 - recall: 0.7760 - auc: 0.9373 - prc: 0.9520"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2970 - tp: 15952.0000 - fp: 1287.0000 - tn: 19055.0000 - fn: 4666.0000 - accuracy: 0.8547 - precision: 0.9253 - recall: 0.7737 - auc: 0.9373 - prc: 0.9520"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2970 - tp: 15952.0000 - fp: 1287.0000 - tn: 19055.0000 - fn: 4666.0000 - accuracy: 0.8547 - precision: 0.9253 - recall: 0.7737 - auc: 0.9373 - prc: 0.9520 - val_loss: 0.1775 - val_tp: 63.0000 - val_fp: 774.0000 - val_tn: 44726.0000 - val_fn: 6.0000 - val_accuracy: 0.9829 - val_precision: 0.0753 - val_recall: 0.9130 - val_auc: 0.9949 - val_prc: 0.7595\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3038 - tp: 770.0000 - fp: 66.0000 - tn: 961.0000 - fn: 251.0000 - accuracy: 0.8452 - precision: 0.9211 - recall: 0.7542 - auc: 0.9331 - prc: 0.9459"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2890 - tp: 3921.0000 - fp: 333.0000 - tn: 4848.0000 - fn: 1138.0000 - accuracy: 0.8563 - precision: 0.9217 - recall: 0.7751 - auc: 0.9394 - prc: 0.9519"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2898 - tp: 6248.0000 - fp: 527.0000 - tn: 7768.0000 - fn: 1841.0000 - accuracy: 0.8555 - precision: 0.9222 - recall: 0.7724 - auc: 0.9400 - prc: 0.9521"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2877 - tp: 8586.0000 - fp: 708.0000 - tn: 10748.0000 - fn: 2486.0000 - accuracy: 0.8582 - precision: 0.9238 - recall: 0.7755 - auc: 0.9407 - prc: 0.9525"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2860 - tp: 10929.0000 - fp: 887.0000 - tn: 13709.0000 - fn: 3147.0000 - accuracy: 0.8593 - precision: 0.9249 - recall: 0.7764 - auc: 0.9417 - prc: 0.9531"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2844 - tp: 13310.0000 - fp: 1045.0000 - tn: 16643.0000 - fn: 3818.0000 - accuracy: 0.8603 - precision: 0.9272 - recall: 0.7771 - auc: 0.9426 - prc: 0.9540"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2834 - tp: 15633.0000 - fp: 1229.0000 - tn: 19595.0000 - fn: 4503.0000 - accuracy: 0.8601 - precision: 0.9271 - recall: 0.7764 - auc: 0.9431 - prc: 0.9542"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2834 - tp: 15633.0000 - fp: 1229.0000 - tn: 19595.0000 - fn: 4503.0000 - accuracy: 0.8601 - precision: 0.9271 - recall: 0.7764 - auc: 0.9431 - prc: 0.9542 - val_loss: 0.1665 - val_tp: 63.0000 - val_fp: 754.0000 - val_tn: 44746.0000 - val_fn: 6.0000 - val_accuracy: 0.9833 - val_precision: 0.0771 - val_recall: 0.9130 - val_auc: 0.9953 - val_prc: 0.7615\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2813 - tp: 784.0000 - fp: 53.0000 - tn: 980.0000 - fn: 231.0000 - accuracy: 0.8613 - precision: 0.9367 - recall: 0.7724 - auc: 0.9463 - prc: 0.9568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2754 - tp: 4014.0000 - fp: 290.0000 - tn: 4804.0000 - fn: 1132.0000 - accuracy: 0.8611 - precision: 0.9326 - recall: 0.7800 - auc: 0.9475 - prc: 0.9590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2778 - tp: 6334.0000 - fp: 472.0000 - tn: 7749.0000 - fn: 1829.0000 - accuracy: 0.8596 - precision: 0.9306 - recall: 0.7759 - auc: 0.9470 - prc: 0.9576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2773 - tp: 8699.0000 - fp: 651.0000 - tn: 10662.0000 - fn: 2516.0000 - accuracy: 0.8594 - precision: 0.9304 - recall: 0.7757 - auc: 0.9471 - prc: 0.9576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2768 - tp: 11096.0000 - fp: 816.0000 - tn: 13574.0000 - fn: 3186.0000 - accuracy: 0.8604 - precision: 0.9315 - recall: 0.7769 - auc: 0.9472 - prc: 0.9579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2760 - tp: 13426.0000 - fp: 1007.0000 - tn: 16528.0000 - fn: 3855.0000 - accuracy: 0.8604 - precision: 0.9302 - recall: 0.7769 - auc: 0.9475 - prc: 0.9578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2778 - tp: 15809.0000 - fp: 1186.0000 - tn: 19384.0000 - fn: 4581.0000 - accuracy: 0.8592 - precision: 0.9302 - recall: 0.7753 - auc: 0.9469 - prc: 0.9576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2778 - tp: 15809.0000 - fp: 1186.0000 - tn: 19384.0000 - fn: 4581.0000 - accuracy: 0.8592 - precision: 0.9302 - recall: 0.7753 - auc: 0.9469 - prc: 0.9576 - val_loss: 0.1567 - val_tp: 63.0000 - val_fp: 738.0000 - val_tn: 44762.0000 - val_fn: 6.0000 - val_accuracy: 0.9837 - val_precision: 0.0787 - val_recall: 0.9130 - val_auc: 0.9957 - val_prc: 0.7651\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2634 - tp: 778.0000 - fp: 52.0000 - tn: 1012.0000 - fn: 206.0000 - accuracy: 0.8740 - precision: 0.9373 - recall: 0.7907 - auc: 0.9533 - prc: 0.9591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2744 - tp: 4033.0000 - fp: 287.0000 - tn: 4789.0000 - fn: 1131.0000 - accuracy: 0.8615 - precision: 0.9336 - recall: 0.7810 - auc: 0.9494 - prc: 0.9598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2743 - tp: 6423.0000 - fp: 487.0000 - tn: 7669.0000 - fn: 1805.0000 - accuracy: 0.8601 - precision: 0.9295 - recall: 0.7806 - auc: 0.9492 - prc: 0.9590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2759 - tp: 8807.0000 - fp: 670.0000 - tn: 10546.0000 - fn: 2505.0000 - accuracy: 0.8591 - precision: 0.9293 - recall: 0.7786 - auc: 0.9484 - prc: 0.9586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2737 - tp: 11134.0000 - fp: 831.0000 - tn: 13527.0000 - fn: 3180.0000 - accuracy: 0.8601 - precision: 0.9305 - recall: 0.7778 - auc: 0.9493 - prc: 0.9588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2710 - tp: 13558.0000 - fp: 975.0000 - tn: 16447.0000 - fn: 3836.0000 - accuracy: 0.8618 - precision: 0.9329 - recall: 0.7795 - auc: 0.9502 - prc: 0.9597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2702 - tp: 15965.0000 - fp: 1113.0000 - tn: 19348.0000 - fn: 4534.0000 - accuracy: 0.8621 - precision: 0.9348 - recall: 0.7788 - auc: 0.9508 - prc: 0.9601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.2702 - tp: 15965.0000 - fp: 1113.0000 - tn: 19348.0000 - fn: 4534.0000 - accuracy: 0.8621 - precision: 0.9348 - recall: 0.7788 - auc: 0.9508 - prc: 0.9601 - val_loss: 0.1489 - val_tp: 63.0000 - val_fp: 738.0000 - val_tn: 44762.0000 - val_fn: 6.0000 - val_accuracy: 0.9837 - val_precision: 0.0787 - val_recall: 0.9130 - val_auc: 0.9960 - val_prc: 0.7679\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2717 - tp: 787.0000 - fp: 61.0000 - tn: 972.0000 - fn: 228.0000 - accuracy: 0.8589 - precision: 0.9281 - recall: 0.7754 - auc: 0.9494 - prc: 0.9589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2589 - tp: 4059.0000 - fp: 278.0000 - tn: 4830.0000 - fn: 1073.0000 - accuracy: 0.8681 - precision: 0.9359 - recall: 0.7909 - auc: 0.9546 - prc: 0.9631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2608 - tp: 6413.0000 - fp: 455.0000 - tn: 7783.0000 - fn: 1733.0000 - accuracy: 0.8665 - precision: 0.9338 - recall: 0.7873 - auc: 0.9543 - prc: 0.9622"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2591 - tp: 8838.0000 - fp: 615.0000 - tn: 10660.0000 - fn: 2415.0000 - accuracy: 0.8655 - precision: 0.9349 - recall: 0.7854 - auc: 0.9552 - prc: 0.9631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2580 - tp: 11231.0000 - fp: 765.0000 - tn: 13606.0000 - fn: 3070.0000 - accuracy: 0.8662 - precision: 0.9362 - recall: 0.7853 - auc: 0.9554 - prc: 0.9633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2579 - tp: 13659.0000 - fp: 913.0000 - tn: 16495.0000 - fn: 3749.0000 - accuracy: 0.8661 - precision: 0.9373 - recall: 0.7846 - auc: 0.9556 - prc: 0.9636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2586 - tp: 16031.0000 - fp: 1081.0000 - tn: 19414.0000 - fn: 4434.0000 - accuracy: 0.8654 - precision: 0.9368 - recall: 0.7833 - auc: 0.9553 - prc: 0.9633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2586 - tp: 16031.0000 - fp: 1081.0000 - tn: 19414.0000 - fn: 4434.0000 - accuracy: 0.8654 - precision: 0.9368 - recall: 0.7833 - auc: 0.9553 - prc: 0.9633 - val_loss: 0.1420 - val_tp: 63.0000 - val_fp: 746.0000 - val_tn: 44754.0000 - val_fn: 6.0000 - val_accuracy: 0.9835 - val_precision: 0.0779 - val_recall: 0.9130 - val_auc: 0.9961 - val_prc: 0.7724\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2465 - tp: 807.0000 - fp: 48.0000 - tn: 982.0000 - fn: 211.0000 - accuracy: 0.8735 - precision: 0.9439 - recall: 0.7927 - auc: 0.9591 - prc: 0.9667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2535 - tp: 3180.0000 - fp: 206.0000 - tn: 3942.0000 - fn: 864.0000 - accuracy: 0.8694 - precision: 0.9392 - recall: 0.7864 - auc: 0.9575 - prc: 0.9641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.2566 - tp: 4787.0000 - fp: 305.0000 - tn: 5876.0000 - fn: 1320.0000 - accuracy: 0.8678 - precision: 0.9401 - recall: 0.7839 - auc: 0.9564 - prc: 0.9636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 9/20 [============>.................] - ETA: 0s - loss: 0.2591 - tp: 7135.0000 - fp: 479.0000 - tn: 8804.0000 - fn: 2014.0000 - accuracy: 0.8647 - precision: 0.9371 - recall: 0.7799 - auc: 0.9557 - prc: 0.9626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2597 - tp: 9541.0000 - fp: 639.0000 - tn: 11716.0000 - fn: 2680.0000 - accuracy: 0.8649 - precision: 0.9372 - recall: 0.7807 - auc: 0.9559 - prc: 0.9628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.2580 - tp: 11985.0000 - fp: 789.0000 - tn: 14604.0000 - fn: 3342.0000 - accuracy: 0.8655 - precision: 0.9382 - recall: 0.7820 - auc: 0.9563 - prc: 0.9635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2573 - tp: 13619.0000 - fp: 877.0000 - tn: 16512.0000 - fn: 3808.0000 - accuracy: 0.8654 - precision: 0.9395 - recall: 0.7815 - auc: 0.9566 - prc: 0.9640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2563 - tp: 15234.0000 - fp: 982.0000 - tn: 18449.0000 - fn: 4247.0000 - accuracy: 0.8656 - precision: 0.9394 - recall: 0.7820 - auc: 0.9569 - prc: 0.9642"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 31ms/step - loss: 0.2562 - tp: 16026.0000 - fp: 1043.0000 - tn: 19414.0000 - fn: 4477.0000 - accuracy: 0.8652 - precision: 0.9389 - recall: 0.7816 - auc: 0.9569 - prc: 0.9641 - val_loss: 0.1360 - val_tp: 64.0000 - val_fp: 744.0000 - val_tn: 44756.0000 - val_fn: 5.0000 - val_accuracy: 0.9836 - val_precision: 0.0792 - val_recall: 0.9275 - val_auc: 0.9962 - val_prc: 0.7750\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2473 - tp: 791.0000 - fp: 51.0000 - tn: 987.0000 - fn: 219.0000 - accuracy: 0.8682 - precision: 0.9394 - recall: 0.7832 - auc: 0.9600 - prc: 0.9659"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2509 - tp: 3951.0000 - fp: 269.0000 - tn: 4912.0000 - fn: 1108.0000 - accuracy: 0.8655 - precision: 0.9363 - recall: 0.7810 - auc: 0.9589 - prc: 0.9648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2480 - tp: 6390.0000 - fp: 401.0000 - tn: 7822.0000 - fn: 1771.0000 - accuracy: 0.8674 - precision: 0.9410 - recall: 0.7830 - auc: 0.9599 - prc: 0.9662"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2471 - tp: 8813.0000 - fp: 551.0000 - tn: 10755.0000 - fn: 2409.0000 - accuracy: 0.8686 - precision: 0.9412 - recall: 0.7853 - auc: 0.9601 - prc: 0.9665"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2476 - tp: 11235.0000 - fp: 721.0000 - tn: 13639.0000 - fn: 3077.0000 - accuracy: 0.8675 - precision: 0.9397 - recall: 0.7850 - auc: 0.9601 - prc: 0.9665"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2469 - tp: 13621.0000 - fp: 860.0000 - tn: 16616.0000 - fn: 3719.0000 - accuracy: 0.8685 - precision: 0.9406 - recall: 0.7855 - auc: 0.9603 - prc: 0.9666"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2461 - tp: 16002.0000 - fp: 1012.0000 - tn: 19574.0000 - fn: 4372.0000 - accuracy: 0.8686 - precision: 0.9405 - recall: 0.7854 - auc: 0.9604 - prc: 0.9667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.2461 - tp: 16002.0000 - fp: 1012.0000 - tn: 19574.0000 - fn: 4372.0000 - accuracy: 0.8686 - precision: 0.9405 - recall: 0.7854 - auc: 0.9604 - prc: 0.9667 - val_loss: 0.1305 - val_tp: 64.0000 - val_fp: 743.0000 - val_tn: 44757.0000 - val_fn: 5.0000 - val_accuracy: 0.9836 - val_precision: 0.0793 - val_recall: 0.9275 - val_auc: 0.9962 - val_prc: 0.7679\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2312 - tp: 832.0000 - fp: 45.0000 - tn: 949.0000 - fn: 222.0000 - accuracy: 0.8696 - precision: 0.9487 - recall: 0.7894 - auc: 0.9682 - prc: 0.9732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2384 - tp: 3243.0000 - fp: 197.0000 - tn: 3884.0000 - fn: 868.0000 - accuracy: 0.8700 - precision: 0.9427 - recall: 0.7889 - auc: 0.9632 - prc: 0.9690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.2441 - tp: 4859.0000 - fp: 316.0000 - tn: 5801.0000 - fn: 1312.0000 - accuracy: 0.8675 - precision: 0.9389 - recall: 0.7874 - auc: 0.9619 - prc: 0.9679"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2429 - tp: 6485.0000 - fp: 404.0000 - tn: 7734.0000 - fn: 1761.0000 - accuracy: 0.8679 - precision: 0.9414 - recall: 0.7864 - auc: 0.9622 - prc: 0.9683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2441 - tp: 8073.0000 - fp: 494.0000 - tn: 9726.0000 - fn: 2187.0000 - accuracy: 0.8691 - precision: 0.9423 - recall: 0.7868 - auc: 0.9621 - prc: 0.9679"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2425 - tp: 9680.0000 - fp: 581.0000 - tn: 11694.0000 - fn: 2621.0000 - accuracy: 0.8697 - precision: 0.9434 - recall: 0.7869 - auc: 0.9626 - prc: 0.9683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2425 - tp: 11320.0000 - fp: 680.0000 - tn: 13616.0000 - fn: 3056.0000 - accuracy: 0.8697 - precision: 0.9433 - recall: 0.7874 - auc: 0.9626 - prc: 0.9683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2427 - tp: 12922.0000 - fp: 777.0000 - tn: 15548.0000 - fn: 3521.0000 - accuracy: 0.8688 - precision: 0.9433 - recall: 0.7859 - auc: 0.9625 - prc: 0.9683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2422 - tp: 14552.0000 - fp: 870.0000 - tn: 17476.0000 - fn: 3966.0000 - accuracy: 0.8688 - precision: 0.9436 - recall: 0.7858 - auc: 0.9626 - prc: 0.9685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2421 - tp: 16160.0000 - fp: 973.0000 - tn: 19431.0000 - fn: 4396.0000 - accuracy: 0.8689 - precision: 0.9432 - recall: 0.7861 - auc: 0.9627 - prc: 0.9685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 34ms/step - loss: 0.2421 - tp: 16160.0000 - fp: 973.0000 - tn: 19431.0000 - fn: 4396.0000 - accuracy: 0.8689 - precision: 0.9432 - recall: 0.7861 - auc: 0.9627 - prc: 0.9685 - val_loss: 0.1254 - val_tp: 64.0000 - val_fp: 743.0000 - val_tn: 44757.0000 - val_fn: 5.0000 - val_accuracy: 0.9836 - val_precision: 0.0793 - val_recall: 0.9275 - val_auc: 0.9962 - val_prc: 0.7700\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 23/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2403 - tp: 793.0000 - fp: 55.0000 - tn: 992.0000 - fn: 208.0000 - accuracy: 0.8716 - precision: 0.9351 - recall: 0.7922 - auc: 0.9616 - prc: 0.9666"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2405 - tp: 3953.0000 - fp: 247.0000 - tn: 4954.0000 - fn: 1086.0000 - accuracy: 0.8698 - precision: 0.9412 - recall: 0.7845 - auc: 0.9630 - prc: 0.9678"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2406 - tp: 6381.0000 - fp: 405.0000 - tn: 7843.0000 - fn: 1755.0000 - accuracy: 0.8682 - precision: 0.9403 - recall: 0.7843 - auc: 0.9629 - prc: 0.9680"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2380 - tp: 8833.0000 - fp: 535.0000 - tn: 10761.0000 - fn: 2399.0000 - accuracy: 0.8698 - precision: 0.9429 - recall: 0.7864 - auc: 0.9639 - prc: 0.9690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2364 - tp: 11234.0000 - fp: 683.0000 - tn: 13707.0000 - fn: 3048.0000 - accuracy: 0.8699 - precision: 0.9427 - recall: 0.7866 - auc: 0.9646 - prc: 0.9694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2358 - tp: 13579.0000 - fp: 834.0000 - tn: 16719.0000 - fn: 3684.0000 - accuracy: 0.8702 - precision: 0.9421 - recall: 0.7866 - auc: 0.9647 - prc: 0.9693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2362 - tp: 16012.0000 - fp: 998.0000 - tn: 19606.0000 - fn: 4344.0000 - accuracy: 0.8696 - precision: 0.9413 - recall: 0.7866 - auc: 0.9645 - prc: 0.9693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2362 - tp: 16012.0000 - fp: 998.0000 - tn: 19606.0000 - fn: 4344.0000 - accuracy: 0.8696 - precision: 0.9413 - recall: 0.7866 - auc: 0.9645 - prc: 0.9693 - val_loss: 0.1207 - val_tp: 65.0000 - val_fp: 744.0000 - val_tn: 44756.0000 - val_fn: 4.0000 - val_accuracy: 0.9836 - val_precision: 0.0803 - val_recall: 0.9420 - val_auc: 0.9962 - val_prc: 0.7720\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2282 - tp: 829.0000 - fp: 51.0000 - tn: 972.0000 - fn: 196.0000 - accuracy: 0.8794 - precision: 0.9420 - recall: 0.8088 - auc: 0.9664 - prc: 0.9714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2303 - tp: 3277.0000 - fp: 183.0000 - tn: 3901.0000 - fn: 831.0000 - accuracy: 0.8762 - precision: 0.9471 - recall: 0.7977 - auc: 0.9667 - prc: 0.9711"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.2284 - tp: 4851.0000 - fp: 274.0000 - tn: 5913.0000 - fn: 1250.0000 - accuracy: 0.8760 - precision: 0.9465 - recall: 0.7951 - auc: 0.9677 - prc: 0.9714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2289 - tp: 6509.0000 - fp: 355.0000 - tn: 7828.0000 - fn: 1692.0000 - accuracy: 0.8751 - precision: 0.9483 - recall: 0.7937 - auc: 0.9677 - prc: 0.9717"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2280 - tp: 8168.0000 - fp: 445.0000 - tn: 9766.0000 - fn: 2101.0000 - accuracy: 0.8757 - precision: 0.9483 - recall: 0.7954 - auc: 0.9681 - prc: 0.9721"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2280 - tp: 9806.0000 - fp: 537.0000 - tn: 11715.0000 - fn: 2518.0000 - accuracy: 0.8757 - precision: 0.9481 - recall: 0.7957 - auc: 0.9679 - prc: 0.9721"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2277 - tp: 11424.0000 - fp: 637.0000 - tn: 13660.0000 - fn: 2951.0000 - accuracy: 0.8749 - precision: 0.9472 - recall: 0.7947 - auc: 0.9679 - prc: 0.9721"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2282 - tp: 13064.0000 - fp: 723.0000 - tn: 15605.0000 - fn: 3376.0000 - accuracy: 0.8749 - precision: 0.9476 - recall: 0.7946 - auc: 0.9677 - prc: 0.9720"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2292 - tp: 14678.0000 - fp: 808.0000 - tn: 17537.0000 - fn: 3841.0000 - accuracy: 0.8739 - precision: 0.9478 - recall: 0.7926 - auc: 0.9675 - prc: 0.9718"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2289 - tp: 16312.0000 - fp: 884.0000 - tn: 19492.0000 - fn: 4272.0000 - accuracy: 0.8741 - precision: 0.9486 - recall: 0.7925 - auc: 0.9675 - prc: 0.9719"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 34ms/step - loss: 0.2289 - tp: 16312.0000 - fp: 884.0000 - tn: 19492.0000 - fn: 4272.0000 - accuracy: 0.8741 - precision: 0.9486 - recall: 0.7925 - auc: 0.9675 - prc: 0.9719 - val_loss: 0.1163 - val_tp: 65.0000 - val_fp: 739.0000 - val_tn: 44761.0000 - val_fn: 4.0000 - val_accuracy: 0.9837 - val_precision: 0.0808 - val_recall: 0.9420 - val_auc: 0.9962 - val_prc: 0.7738\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2191 - tp: 772.0000 - fp: 46.0000 - tn: 1025.0000 - fn: 205.0000 - accuracy: 0.8774 - precision: 0.9438 - recall: 0.7902 - auc: 0.9714 - prc: 0.9726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2237 - tp: 3231.0000 - fp: 176.0000 - tn: 3928.0000 - fn: 857.0000 - accuracy: 0.8739 - precision: 0.9483 - recall: 0.7904 - auc: 0.9695 - prc: 0.9734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.2250 - tp: 4903.0000 - fp: 263.0000 - tn: 5834.0000 - fn: 1288.0000 - accuracy: 0.8738 - precision: 0.9491 - recall: 0.7920 - auc: 0.9690 - prc: 0.9734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 9/20 [============>.................] - ETA: 0s - loss: 0.2259 - tp: 7361.0000 - fp: 397.0000 - tn: 8738.0000 - fn: 1936.0000 - accuracy: 0.8734 - precision: 0.9488 - recall: 0.7918 - auc: 0.9690 - prc: 0.9733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2260 - tp: 9798.0000 - fp: 535.0000 - tn: 11670.0000 - fn: 2573.0000 - accuracy: 0.8735 - precision: 0.9482 - recall: 0.7920 - auc: 0.9690 - prc: 0.9732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.2263 - tp: 12279.0000 - fp: 656.0000 - tn: 14560.0000 - fn: 3225.0000 - accuracy: 0.8737 - precision: 0.9493 - recall: 0.7920 - auc: 0.9689 - prc: 0.9732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2250 - tp: 14753.0000 - fp: 806.0000 - tn: 17478.0000 - fn: 3827.0000 - accuracy: 0.8743 - precision: 0.9482 - recall: 0.7940 - auc: 0.9692 - prc: 0.9733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2256 - tp: 16361.0000 - fp: 889.0000 - tn: 19458.0000 - fn: 4252.0000 - accuracy: 0.8745 - precision: 0.9485 - recall: 0.7937 - auc: 0.9690 - prc: 0.9730 - val_loss: 0.1134 - val_tp: 66.0000 - val_fp: 756.0000 - val_tn: 44744.0000 - val_fn: 3.0000 - val_accuracy: 0.9833 - val_precision: 0.0803 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7748\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 26/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2184 - tp: 821.0000 - fp: 48.0000 - tn: 967.0000 - fn: 212.0000 - accuracy: 0.8730 - precision: 0.9448 - recall: 0.7948 - auc: 0.9700 - prc: 0.9742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2221 - tp: 4049.0000 - fp: 241.0000 - tn: 4875.0000 - fn: 1075.0000 - accuracy: 0.8715 - precision: 0.9438 - recall: 0.7902 - auc: 0.9699 - prc: 0.9730"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2236 - tp: 6526.0000 - fp: 377.0000 - tn: 7755.0000 - fn: 1726.0000 - accuracy: 0.8716 - precision: 0.9454 - recall: 0.7908 - auc: 0.9693 - prc: 0.9733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2210 - tp: 8971.0000 - fp: 508.0000 - tn: 10731.0000 - fn: 2318.0000 - accuracy: 0.8746 - precision: 0.9464 - recall: 0.7947 - auc: 0.9697 - prc: 0.9736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2216 - tp: 10571.0000 - fp: 578.0000 - tn: 12703.0000 - fn: 2772.0000 - accuracy: 0.8742 - precision: 0.9482 - recall: 0.7923 - auc: 0.9697 - prc: 0.9736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.2206 - tp: 12195.0000 - fp: 661.0000 - tn: 14671.0000 - fn: 3193.0000 - accuracy: 0.8745 - precision: 0.9486 - recall: 0.7925 - auc: 0.9700 - prc: 0.9739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2203 - tp: 13817.0000 - fp: 746.0000 - tn: 16652.0000 - fn: 3601.0000 - accuracy: 0.8751 - precision: 0.9488 - recall: 0.7933 - auc: 0.9701 - prc: 0.9738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2206 - tp: 15427.0000 - fp: 847.0000 - tn: 18623.0000 - fn: 4015.0000 - accuracy: 0.8751 - precision: 0.9480 - recall: 0.7935 - auc: 0.9701 - prc: 0.9737"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 31ms/step - loss: 0.2208 - tp: 16267.0000 - fp: 893.0000 - tn: 19573.0000 - fn: 4227.0000 - accuracy: 0.8750 - precision: 0.9480 - recall: 0.7937 - auc: 0.9700 - prc: 0.9737 - val_loss: 0.1106 - val_tp: 66.0000 - val_fp: 762.0000 - val_tn: 44738.0000 - val_fn: 3.0000 - val_accuracy: 0.9832 - val_precision: 0.0797 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7758\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 27/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2157 - tp: 871.0000 - fp: 44.0000 - tn: 921.0000 - fn: 212.0000 - accuracy: 0.8750 - precision: 0.9519 - recall: 0.8042 - auc: 0.9730 - prc: 0.9774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2177 - tp: 3296.0000 - fp: 147.0000 - tn: 3884.0000 - fn: 865.0000 - accuracy: 0.8765 - precision: 0.9573 - recall: 0.7921 - auc: 0.9724 - prc: 0.9756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 6/20 [========>.....................] - ETA: 0s - loss: 0.2164 - tp: 4927.0000 - fp: 214.0000 - tn: 5867.0000 - fn: 1280.0000 - accuracy: 0.8784 - precision: 0.9584 - recall: 0.7938 - auc: 0.9726 - prc: 0.9756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2165 - tp: 6566.0000 - fp: 307.0000 - tn: 7839.0000 - fn: 1672.0000 - accuracy: 0.8792 - precision: 0.9553 - recall: 0.7970 - auc: 0.9722 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2166 - tp: 8181.0000 - fp: 386.0000 - tn: 9787.0000 - fn: 2126.0000 - accuracy: 0.8773 - precision: 0.9549 - recall: 0.7937 - auc: 0.9724 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2174 - tp: 9811.0000 - fp: 483.0000 - tn: 11736.0000 - fn: 2546.0000 - accuracy: 0.8767 - precision: 0.9531 - recall: 0.7940 - auc: 0.9720 - prc: 0.9751"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2180 - tp: 11400.0000 - fp: 590.0000 - tn: 13736.0000 - fn: 2946.0000 - accuracy: 0.8767 - precision: 0.9508 - recall: 0.7946 - auc: 0.9716 - prc: 0.9746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2179 - tp: 13027.0000 - fp: 677.0000 - tn: 15707.0000 - fn: 3357.0000 - accuracy: 0.8769 - precision: 0.9506 - recall: 0.7951 - auc: 0.9715 - prc: 0.9745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2174 - tp: 14617.0000 - fp: 774.0000 - tn: 17699.0000 - fn: 3774.0000 - accuracy: 0.8766 - precision: 0.9497 - recall: 0.7948 - auc: 0.9716 - prc: 0.9745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2170 - tp: 16197.0000 - fp: 864.0000 - tn: 19723.0000 - fn: 4176.0000 - accuracy: 0.8770 - precision: 0.9494 - recall: 0.7950 - auc: 0.9717 - prc: 0.9745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 34ms/step - loss: 0.2170 - tp: 16197.0000 - fp: 864.0000 - tn: 19723.0000 - fn: 4176.0000 - accuracy: 0.8770 - precision: 0.9494 - recall: 0.7950 - auc: 0.9717 - prc: 0.9745 - val_loss: 0.1082 - val_tp: 66.0000 - val_fp: 774.0000 - val_tn: 44726.0000 - val_fn: 3.0000 - val_accuracy: 0.9829 - val_precision: 0.0786 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7769\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2214 - tp: 807.0000 - fp: 51.0000 - tn: 984.0000 - fn: 206.0000 - accuracy: 0.8745 - precision: 0.9406 - recall: 0.7966 - auc: 0.9700 - prc: 0.9730"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2193 - tp: 3251.0000 - fp: 186.0000 - tn: 3918.0000 - fn: 837.0000 - accuracy: 0.8751 - precision: 0.9459 - recall: 0.7953 - auc: 0.9706 - prc: 0.9736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.2157 - tp: 5713.0000 - fp: 289.0000 - tn: 6849.0000 - fn: 1485.0000 - accuracy: 0.8763 - precision: 0.9518 - recall: 0.7937 - auc: 0.9722 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2164 - tp: 8131.0000 - fp: 457.0000 - tn: 9816.0000 - fn: 2076.0000 - accuracy: 0.8763 - precision: 0.9468 - recall: 0.7966 - auc: 0.9712 - prc: 0.9742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2183 - tp: 10582.0000 - fp: 597.0000 - tn: 12720.0000 - fn: 2725.0000 - accuracy: 0.8752 - precision: 0.9466 - recall: 0.7952 - auc: 0.9710 - prc: 0.9742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2164 - tp: 13076.0000 - fp: 714.0000 - tn: 15641.0000 - fn: 3337.0000 - accuracy: 0.8764 - precision: 0.9482 - recall: 0.7967 - auc: 0.9716 - prc: 0.9748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2145 - tp: 15532.0000 - fp: 824.0000 - tn: 18604.0000 - fn: 3952.0000 - accuracy: 0.8773 - precision: 0.9496 - recall: 0.7972 - auc: 0.9722 - prc: 0.9753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2147 - tp: 16390.0000 - fp: 867.0000 - tn: 19544.0000 - fn: 4159.0000 - accuracy: 0.8773 - precision: 0.9498 - recall: 0.7976 - auc: 0.9721 - prc: 0.9754 - val_loss: 0.1051 - val_tp: 66.0000 - val_fp: 774.0000 - val_tn: 44726.0000 - val_fn: 3.0000 - val_accuracy: 0.9829 - val_precision: 0.0786 - val_recall: 0.9565 - val_auc: 0.9961 - val_prc: 0.7771\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 29/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2115 - tp: 804.0000 - fp: 62.0000 - tn: 989.0000 - fn: 193.0000 - accuracy: 0.8755 - precision: 0.9284 - recall: 0.8064 - auc: 0.9724 - prc: 0.9738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2110 - tp: 3239.0000 - fp: 184.0000 - tn: 3944.0000 - fn: 825.0000 - accuracy: 0.8768 - precision: 0.9462 - recall: 0.7970 - auc: 0.9727 - prc: 0.9752"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.2117 - tp: 5669.0000 - fp: 307.0000 - tn: 6879.0000 - fn: 1481.0000 - accuracy: 0.8753 - precision: 0.9486 - recall: 0.7929 - auc: 0.9731 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2096 - tp: 8108.0000 - fp: 439.0000 - tn: 9865.0000 - fn: 2068.0000 - accuracy: 0.8776 - precision: 0.9486 - recall: 0.7968 - auc: 0.9736 - prc: 0.9762"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2104 - tp: 9710.0000 - fp: 516.0000 - tn: 11856.0000 - fn: 2494.0000 - accuracy: 0.8775 - precision: 0.9495 - recall: 0.7956 - auc: 0.9736 - prc: 0.9761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2108 - tp: 11293.0000 - fp: 605.0000 - tn: 13902.0000 - fn: 2872.0000 - accuracy: 0.8787 - precision: 0.9492 - recall: 0.7972 - auc: 0.9734 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2103 - tp: 12906.0000 - fp: 696.0000 - tn: 15892.0000 - fn: 3274.0000 - accuracy: 0.8788 - precision: 0.9488 - recall: 0.7977 - auc: 0.9735 - prc: 0.9758"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2097 - tp: 15354.0000 - fp: 816.0000 - tn: 18899.0000 - fn: 3843.0000 - accuracy: 0.8803 - precision: 0.9495 - recall: 0.7998 - auc: 0.9737 - prc: 0.9760"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 31ms/step - loss: 0.2100 - tp: 16237.0000 - fp: 868.0000 - tn: 19885.0000 - fn: 3970.0000 - accuracy: 0.8819 - precision: 0.9493 - recall: 0.8035 - auc: 0.9737 - prc: 0.9759 - val_loss: 0.1026 - val_tp: 66.0000 - val_fp: 785.0000 - val_tn: 44715.0000 - val_fn: 3.0000 - val_accuracy: 0.9827 - val_precision: 0.0776 - val_recall: 0.9565 - val_auc: 0.9960 - val_prc: 0.7781\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 30/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2075 - tp: 863.0000 - fp: 59.0000 - tn: 1004.0000 - fn: 122.0000 - accuracy: 0.9116 - precision: 0.9360 - recall: 0.8761 - auc: 0.9736 - prc: 0.9749"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2130 - tp: 4475.0000 - fp: 269.0000 - tn: 4877.0000 - fn: 619.0000 - accuracy: 0.9133 - precision: 0.9433 - recall: 0.8785 - auc: 0.9730 - prc: 0.9756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2117 - tp: 7173.0000 - fp: 424.0000 - tn: 7777.0000 - fn: 1010.0000 - accuracy: 0.9125 - precision: 0.9442 - recall: 0.8766 - auc: 0.9731 - prc: 0.9759"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2114 - tp: 9847.0000 - fp: 567.0000 - tn: 10705.0000 - fn: 1409.0000 - accuracy: 0.9123 - precision: 0.9456 - recall: 0.8748 - auc: 0.9735 - prc: 0.9761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2108 - tp: 12560.0000 - fp: 719.0000 - tn: 13612.0000 - fn: 1781.0000 - accuracy: 0.9128 - precision: 0.9459 - recall: 0.8758 - auc: 0.9738 - prc: 0.9763"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2116 - tp: 15242.0000 - fp: 885.0000 - tn: 16532.0000 - fn: 2157.0000 - accuracy: 0.9126 - precision: 0.9451 - recall: 0.8760 - auc: 0.9735 - prc: 0.9760"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2117 - tp: 17870.0000 - fp: 1046.0000 - tn: 19512.0000 - fn: 2532.0000 - accuracy: 0.9126 - precision: 0.9447 - recall: 0.8759 - auc: 0.9734 - prc: 0.9757"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2117 - tp: 17870.0000 - fp: 1046.0000 - tn: 19512.0000 - fn: 2532.0000 - accuracy: 0.9126 - precision: 0.9447 - recall: 0.8759 - auc: 0.9734 - prc: 0.9757 - val_loss: 0.1003 - val_tp: 66.0000 - val_fp: 790.0000 - val_tn: 44710.0000 - val_fn: 3.0000 - val_accuracy: 0.9826 - val_precision: 0.0771 - val_recall: 0.9565 - val_auc: 0.9960 - val_prc: 0.7791\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 31/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1965 - tp: 891.0000 - fp: 42.0000 - tn: 998.0000 - fn: 117.0000 - accuracy: 0.9224 - precision: 0.9550 - recall: 0.8839 - auc: 0.9777 - prc: 0.9797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2078 - tp: 4479.0000 - fp: 233.0000 - tn: 4890.0000 - fn: 638.0000 - accuracy: 0.9149 - precision: 0.9506 - recall: 0.8753 - auc: 0.9745 - prc: 0.9773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2057 - tp: 7161.0000 - fp: 381.0000 - tn: 7830.0000 - fn: 1012.0000 - accuracy: 0.9150 - precision: 0.9495 - recall: 0.8762 - auc: 0.9750 - prc: 0.9776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2046 - tp: 9873.0000 - fp: 549.0000 - tn: 10743.0000 - fn: 1363.0000 - accuracy: 0.9151 - precision: 0.9473 - recall: 0.8787 - auc: 0.9752 - prc: 0.9777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2039 - tp: 11717.0000 - fp: 657.0000 - tn: 12654.0000 - fn: 1596.0000 - accuracy: 0.9154 - precision: 0.9469 - recall: 0.8801 - auc: 0.9753 - prc: 0.9778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.2028 - tp: 13531.0000 - fp: 741.0000 - tn: 14627.0000 - fn: 1821.0000 - accuracy: 0.9166 - precision: 0.9481 - recall: 0.8814 - auc: 0.9758 - prc: 0.9782"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2031 - tp: 16184.0000 - fp: 898.0000 - tn: 17603.0000 - fn: 2179.0000 - accuracy: 0.9165 - precision: 0.9474 - recall: 0.8813 - auc: 0.9758 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2027 - tp: 18028.0000 - fp: 1001.0000 - tn: 19511.0000 - fn: 2420.0000 - accuracy: 0.9165 - precision: 0.9474 - recall: 0.8817 - auc: 0.9759 - prc: 0.9781 - val_loss: 0.0977 - val_tp: 66.0000 - val_fp: 782.0000 - val_tn: 44718.0000 - val_fn: 3.0000 - val_accuracy: 0.9828 - val_precision: 0.0778 - val_recall: 0.9565 - val_auc: 0.9959 - val_prc: 0.7807\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 32/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2094 - tp: 941.0000 - fp: 48.0000 - tn: 932.0000 - fn: 127.0000 - accuracy: 0.9146 - precision: 0.9515 - recall: 0.8811 - auc: 0.9752 - prc: 0.9782"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2016 - tp: 3641.0000 - fp: 207.0000 - tn: 3885.0000 - fn: 459.0000 - accuracy: 0.9187 - precision: 0.9462 - recall: 0.8880 - auc: 0.9765 - prc: 0.9785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.2021 - tp: 6380.0000 - fp: 351.0000 - tn: 6813.0000 - fn: 792.0000 - accuracy: 0.9203 - precision: 0.9479 - recall: 0.8896 - auc: 0.9769 - prc: 0.9788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2036 - tp: 9159.0000 - fp: 504.0000 - tn: 9687.0000 - fn: 1130.0000 - accuracy: 0.9202 - precision: 0.9478 - recall: 0.8902 - auc: 0.9763 - prc: 0.9784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2025 - tp: 11832.0000 - fp: 647.0000 - tn: 12667.0000 - fn: 1478.0000 - accuracy: 0.9202 - precision: 0.9482 - recall: 0.8890 - auc: 0.9764 - prc: 0.9784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2036 - tp: 14527.0000 - fp: 809.0000 - tn: 15579.0000 - fn: 1853.0000 - accuracy: 0.9188 - precision: 0.9472 - recall: 0.8869 - auc: 0.9761 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2033 - tp: 17221.0000 - fp: 953.0000 - tn: 18535.0000 - fn: 2203.0000 - accuracy: 0.9189 - precision: 0.9476 - recall: 0.8866 - auc: 0.9762 - prc: 0.9780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2036 - tp: 18110.0000 - fp: 1003.0000 - tn: 19526.0000 - fn: 2321.0000 - accuracy: 0.9188 - precision: 0.9475 - recall: 0.8864 - auc: 0.9761 - prc: 0.9780 - val_loss: 0.0956 - val_tp: 66.0000 - val_fp: 789.0000 - val_tn: 44711.0000 - val_fn: 3.0000 - val_accuracy: 0.9826 - val_precision: 0.0772 - val_recall: 0.9565 - val_auc: 0.9959 - val_prc: 0.7723\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2145 - tp: 907.0000 - fp: 66.0000 - tn: 963.0000 - fn: 112.0000 - accuracy: 0.9131 - precision: 0.9322 - recall: 0.8901 - auc: 0.9750 - prc: 0.9754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2020 - tp: 4565.0000 - fp: 257.0000 - tn: 4867.0000 - fn: 551.0000 - accuracy: 0.9211 - precision: 0.9467 - recall: 0.8923 - auc: 0.9778 - prc: 0.9789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.1995 - tp: 7291.0000 - fp: 395.0000 - tn: 7795.0000 - fn: 903.0000 - accuracy: 0.9208 - precision: 0.9486 - recall: 0.8898 - auc: 0.9780 - prc: 0.9794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.1999 - tp: 10018.0000 - fp: 534.0000 - tn: 10728.0000 - fn: 1248.0000 - accuracy: 0.9209 - precision: 0.9494 - recall: 0.8892 - auc: 0.9778 - prc: 0.9793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2003 - tp: 12739.0000 - fp: 688.0000 - tn: 13642.0000 - fn: 1603.0000 - accuracy: 0.9201 - precision: 0.9488 - recall: 0.8882 - auc: 0.9775 - prc: 0.9790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.1998 - tp: 15480.0000 - fp: 843.0000 - tn: 16568.0000 - fn: 1925.0000 - accuracy: 0.9205 - precision: 0.9484 - recall: 0.8894 - auc: 0.9775 - prc: 0.9789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2003 - tp: 18169.0000 - fp: 1012.0000 - tn: 19520.0000 - fn: 2259.0000 - accuracy: 0.9201 - precision: 0.9472 - recall: 0.8894 - auc: 0.9773 - prc: 0.9786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 23.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2003 - tp: 18169.0000 - fp: 1012.0000 - tn: 19520.0000 - fn: 2259.0000 - accuracy: 0.9201 - precision: 0.9472 - recall: 0.8894 - auc: 0.9773 - prc: 0.9786 - val_loss: 0.0931 - val_tp: 66.0000 - val_fp: 780.0000 - val_tn: 44720.0000 - val_fn: 3.0000 - val_accuracy: 0.9828 - val_precision: 0.0780 - val_recall: 0.9565 - val_auc: 0.9959 - val_prc: 0.7733\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33: early stopping\n"
     ]
    }
   ],
   "source": [
    "resampled_model = make_model()\n",
    "resampled_model.load_weights(initial_weights)\n",
    "\n",
    "# Reset the bias to zero, since this dataset is balanced.\n",
    "output_layer = resampled_model.layers[-1] \n",
    "output_layer.bias.assign([0])\n",
    "\n",
    "resampled_history = resampled_model.fit(\n",
    "    resampled_ds,\n",
    "    # These are not real epochs\n",
    "    steps_per_epoch = 20,\n",
    "    epochs=10*EPOCHS,\n",
    "    callbacks = [early_stopping],\n",
    "    validation_data=(val_ds))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UuJYKv0gpBK1"
   },
   "source": [
    "### 重新查看训练历史记录"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:19:17.974680Z",
     "iopub.status.busy": "2023-11-08T01:19:17.974389Z",
     "iopub.status.idle": "2023-11-08T01:19:18.688630Z",
     "shell.execute_reply": "2023-11-08T01:19:18.687793Z"
    },
    "id": "FMycrpJwn39w"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_metrics(resampled_history)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bUuE5HOWZiwP"
   },
   "source": [
    "### 评估指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:19:18.693138Z",
     "iopub.status.busy": "2023-11-08T01:19:18.692844Z",
     "iopub.status.idle": "2023-11-08T01:19:19.193142Z",
     "shell.execute_reply": "2023-11-08T01:19:19.192145Z"
    },
    "id": "C0fmHSgXxFdW"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 8s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "34/90 [==========>...................] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "69/90 [======================>.......] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "90/90 [==============================] - 0s 1ms/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/28 [>.............................] - ETA: 1s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "28/28 [==============================] - 0s 1ms/step\n"
     ]
    }
   ],
   "source": [
    "train_predictions_resampled = resampled_model.predict(train_features, batch_size=BATCH_SIZE)\n",
    "test_predictions_resampled = resampled_model.predict(test_features, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:19:19.197804Z",
     "iopub.status.busy": "2023-11-08T01:19:19.197055Z",
     "iopub.status.idle": "2023-11-08T01:19:20.053204Z",
     "shell.execute_reply": "2023-11-08T01:19:20.052471Z"
    },
    "id": "FO0mMOYUDWFk"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.12108473479747772\n",
      "tp :  95.0\n",
      "fp :  915.0\n",
      "tn :  55940.0\n",
      "fn :  12.0\n",
      "accuracy :  0.9837259650230408\n",
      "precision :  0.09405940771102905\n",
      "recall :  0.8878504633903503\n",
      "auc :  0.9800193309783936\n",
      "prc :  0.7522088289260864\n",
      "\n",
      "Legitimate Transactions Detected (True Negatives):  55940\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  915\n",
      "Fraudulent Transactions Missed (False Negatives):  12\n",
      "Fraudulent Transactions Detected (True Positives):  95\n",
      "Total Fraudulent Transactions:  107\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resampled_results = resampled_model.evaluate(test_features, test_labels,\n",
    "                                             batch_size=BATCH_SIZE, verbose=0)\n",
    "for name, value in zip(resampled_model.metrics_names, resampled_results):\n",
    "  print(name, ': ', value)\n",
    "print()\n",
    "\n",
    "plot_cm(test_labels, test_predictions_resampled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_xYozM1IIITq"
   },
   "source": [
    "### 绘制 ROC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:19:20.057279Z",
     "iopub.status.busy": "2023-11-08T01:19:20.056969Z",
     "iopub.status.idle": "2023-11-08T01:19:20.477726Z",
     "shell.execute_reply": "2023-11-08T01:19:20.476891Z"
    },
    "id": "fye_CiuYrZ1U"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "\n",
    "plot_roc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
    "plot_roc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
    "\n",
    "plot_roc(\"Train Resampled\", train_labels, train_predictions_resampled, color=colors[2])\n",
    "plot_roc(\"Test Resampled\", test_labels, test_predictions_resampled, color=colors[2], linestyle='--')\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vayGnv0VOe_v"
   },
   "source": [
    "### 绘制 AUPRC\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T01:19:20.482084Z",
     "iopub.status.busy": "2023-11-08T01:19:20.481792Z",
     "iopub.status.idle": "2023-11-08T01:19:20.947932Z",
     "shell.execute_reply": "2023-11-08T01:19:20.947052Z"
    },
    "id": "wgWXQ8aeOhCZ"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
    "\n",
    "plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
    "plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
    "\n",
    "plot_prc(\"Train Resampled\", train_labels, train_predictions_resampled, color=colors[2])\n",
    "plot_prc(\"Test Resampled\", test_labels, test_predictions_resampled, color=colors[2], linestyle='--')\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3o3f0ywl8uqW"
   },
   "source": [
    "## 使用本教程解决您的问题\n",
    "\n",
    "由于可供学习的样本过少，不平衡数据的分类是固有难题。您应该始终先从数据开始，尽可能多地收集样本，并充分考虑可能相关的特征，以便模型能够充分利用占少数的类。有时您的模型可能难以改善且无法获得想要的结果，因此请务必牢记问题的上下文，并在不同类型的错误之间进行权衡。"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "imbalanced_data.ipynb",
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}