{
 "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": "2022-12-14T23:05:43.773601Z",
     "iopub.status.busy": "2022-12-14T23:05:43.773150Z",
     "iopub.status.idle": "2022-12-14T23:05:43.776665Z",
     "shell.execute_reply": "2022-12-14T23:05:43.776156Z"
    },
    "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": [
    "# 不均衡データの分類"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DwdpaTKJOoPu"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td><a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/structured_data/imbalanced_data\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\">TensorFlow.org で表示</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs-l10n/blob/master/site/ja/tutorials/structured_data/imbalanced_data.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\">Google Colab で実行</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/docs-l10n/blob/master/site/ja/tutorials/structured_data/imbalanced_data.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\">GitHub でソースを表示</a></td>\n",
    "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/docs-l10n/site/ja/tutorials/structured_data/imbalanced_data.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\">ノートブックをダウンロード</a></td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mthoSGBAOoX-"
   },
   "source": [
    "このチュートリアルでは、1 つのクラスの例の数が他のクラスの例の数を大幅に上回る、非常に不均衡なデータセットを分類する方法を示します。Kaggle でホストされている[クレジットカード不正検出](https://www.kaggle.com/mlg-ulb/creditcardfraud)データセットを使用します。目的は、合計 284,807 件のトランザクションからわずか 492 件の不正なトランザクションを検出することです。[Keras](https://www.tensorflow.org/guide/keras/overview) を使用してモデルを定義し、[クラスの重み付け](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/Model)を使用してモデルが不均衡なデータから学習できるようにします。\n",
    "\n",
    "このチュートリアルには、次の完全なコードが含まれています。\n",
    "\n",
    "- Pandas を使用して CSV ファイルを読み込む。\n",
    "- トレーニングセット、検証セット、テストセットを作成する。\n",
    "- Keras を使用してモデルの定義してトレーニングする（クラスの重みの設定を含む）。\n",
    "- 様々なメトリクス（適合率や再現率を含む）を使用してモデルを評価する。\n",
    "- 不均衡データを扱うための一般的なテクニックを試す。\n",
    "    - クラスの重み付け\n",
    "    - オーバーサンプリング\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kRHmSyHxEIhN"
   },
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:43.780179Z",
     "iopub.status.busy": "2022-12-14T23:05:43.779740Z",
     "iopub.status.idle": "2022-12-14T23:05:46.330369Z",
     "shell.execute_reply": "2022-12-14T23:05:46.329697Z"
    },
    "id": "JM7hDSNClfoK"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-14 23:05:44.726441: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2022-12-14 23:05:44.726537: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2022-12-14 23:05:44.726547: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\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": "2022-12-14T23:05:46.334408Z",
     "iopub.status.busy": "2022-12-14T23:05:46.333989Z",
     "iopub.status.idle": "2022-12-14T23:05:46.337628Z",
     "shell.execute_reply": "2022-12-14T23:05:46.337066Z"
    },
    "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": [
    "## データの処理と調査"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4sA9WOcmzH2D"
   },
   "source": [
    "### Kaggle Credit Card Fraud データセットをダウンロードする\n",
    "\n",
    "[Pandas](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame) は、構造化データの読み込みと処理を支援するユーティリティが多数含まれる Python ライブラリです。Pandas を使用し、URL から CSV を Pandas [DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame) にダウンロードします。\n",
    "\n",
    "注意: このデータセットは、Worldline と ULB (Université Libre de Bruxelles) の[機械学習グループ](http://mlg.ulb.ac.be)によるビッグデータマイニングと不正検出に関する共同研究で収集および分析されたものです。関連トピックに関する現在および過去のプロジェクトの詳細は、[こちら](https://www.researchgate.net/project/Fraud-detection-5)と [DefeatFraud](https://mlg.ulb.ac.be/wordpress/portfolio_page/defeatfraud-assessment-and-validation-of-deep-feature-engineering-and-learning-solutions-for-fraud-detection/) プロジェクトのページをご覧ください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:46.340799Z",
     "iopub.status.busy": "2022-12-14T23:05:46.340359Z",
     "iopub.status.idle": "2022-12-14T23:05:48.697197Z",
     "shell.execute_reply": "2022-12-14T23:05:48.696568Z"
    },
    "id": "pR_SnbMArXr7"
   },
   "outputs": [
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       "      <td>0.247998</td>\n",
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       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\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",
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       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
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       "      <td>-0.108300</td>\n",
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       "      <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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       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
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       "\n",
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       "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": "2022-12-14T23:05:48.700291Z",
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   "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",
       "    </tr>\n",
       "    <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": [
    "### クラスラベルの不均衡を調べる\n",
    "\n",
    "データセットの不均衡を見てみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:48.847906Z",
     "iopub.status.busy": "2022-12-14T23:05:48.847290Z",
     "iopub.status.idle": "2022-12-14T23:05:48.852246Z",
     "shell.execute_reply": "2022-12-14T23:05:48.851599Z"
    },
    "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": [
    "これは、陽性サンプルの割合が少ないことを示しています。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6qox6ryyzwdr"
   },
   "source": [
    "### データをクリーニング、分割、正規化する\n",
    "\n",
    "生データにはいくつかの問題があります。まず、`Time`カラムと`Amount`カラムはむらがあり過ぎてそのままでは使用できません。`Time`カラムは意味が明確ではないため削除し、`Amount`カラムのログを取って範囲を縮小します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:48.855675Z",
     "iopub.status.busy": "2022-12-14T23:05:48.855097Z",
     "iopub.status.idle": "2022-12-14T23:05:48.892323Z",
     "shell.execute_reply": "2022-12-14T23:05:48.891654Z"
    },
    "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": [
    "データセットをトレーニングセット、検証セット、テストセットに分割します。検証セットはモデルを適合させる間に使用され、損失とメトリクスを評価しますが、モデルはこのデータに適合しません。テストセットはトレーニング段階では全く使用されず、モデルがどの程度新しいデータを一般化したかを評価するために最後にだけ使用されます。これはトレーニングデータ不足による[過学習](https://developers.google.com/machine-learning/crash-course/generalization/peril-of-overfitting)が重大な懸念事項である不均衡データセットでは特に重要です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:48.896163Z",
     "iopub.status.busy": "2022-12-14T23:05:48.895569Z",
     "iopub.status.idle": "2022-12-14T23:05:49.120366Z",
     "shell.execute_reply": "2022-12-14T23:05:49.119591Z"
    },
    "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": [
    "sklearn の StandardScaler を使用して入力特徴を正規化します。これで平均は 0、標準偏差は 1 に設定されます。\n",
    "\n",
    "注意: `StandardScaler`は`train_features`を使用する場合にのみ適合し、モデルが検証セットやテストセットでピークを迎えることがないようにします。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:49.124767Z",
     "iopub.status.busy": "2022-12-14T23:05:49.124169Z",
     "iopub.status.idle": "2022-12-14T23:05:49.237042Z",
     "shell.execute_reply": "2022-12-14T23:05:49.236358Z"
    },
    "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": [
    "警告: モデルをデプロイする場合には、前処理の計算を保存することが非常に重要です。最も簡単なのは、それらをレイヤーとして実装し、エクスポート前にモデルに加える方法です。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uQ7m9nqDC3W6"
   },
   "source": [
    "### データ分散を確認する\n",
    "\n",
    "次に、いくつかの特徴における陽性の例と陰性の例の分散を比較します。 この時点で自問すべき点は、次のとおりです。\n",
    "\n",
    "- それらの分散には意味がありますか？\n",
    "    - はい。入力を正規化したので、ほとんどが`+/- 2`の範囲内に集中しています。\n",
    "- 分散間の差は見られますか？\n",
    "    - はい。陽性の例には、はるかに高い極値が含まれています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:49.240800Z",
     "iopub.status.busy": "2022-12-14T23:05:49.240158Z",
     "iopub.status.idle": "2022-12-14T23:05:50.939846Z",
     "shell.execute_reply": "2022-12-14T23:05:50.939168Z"
    },
    "id": "raK7hyjd_vf6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "## モデルとメトリクスを定義する\n",
    "\n",
    "密に接続された非表示レイヤー、過学習を防ぐ[ドロップアウト](https://developers.google.com/machine-learning/glossary/#dropout_regularization)レイヤー、取引が不正である確率を返す出力シグモイドレイヤーを持つ単純なニューラルネットワークを作成する関数を定義します。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:50.943407Z",
     "iopub.status.busy": "2022-12-14T23:05:50.942784Z",
     "iopub.status.idle": "2022-12-14T23:05:54.281741Z",
     "shell.execute_reply": "2022-12-14T23:05:54.280902Z"
    },
    "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": [
    "### 有用なメトリクスを理解する\n",
    "\n",
    "上記で定義したメトリクスのいくつかは、モデルで計算できるため、パフォーマンス評価の際に有用なことに着目してください。\n",
    "\n",
    "- **偽**陰性と**偽**陽性は**誤って**分類されたサンプルです。\n",
    "- **真**陰性と**真**陽性は**正しく**分類されたサンプルです。\n",
    "- **正解率**は正しく分類された例の割合です。\n",
    "\n",
    "> $\\frac{\\text{true samples}}{\\text{total samples}}$\n",
    "\n",
    "- **適合率**は正しく分類された**予測**陽性の割合です。\n",
    "\n",
    "> $\\frac{\\text{true positives}}{\\text{true positives + false positives}}$\n",
    "\n",
    "- **再現率**は正しく分類された**実際の**陽性の割合です。\n",
    "\n",
    "> $\\frac{\\text{true positives}}{\\text{true positives + false negatives}}$\n",
    "\n",
    "- **AUC** は受信者動作特性曲線 (ROC-AUC) の曲線下の面積を指します。この指標は、分類器がランダムな正のサンプルをランダムな負のサンプルよりも高くランク付けする確率に等しくなります。\n",
    "- **AUPRC** は適合率-再現率曲線の曲線下の面積を指します。この指標は、さまざまな確率しきい値の適合率と再現率のペアを計算します。\n",
    "\n",
    "注意: 精度は、このタスクに役立つ指標ではありません。常に False を予測することで、このタスクの精度を 99.8％ 以上にすることができるからです。\n",
    "\n",
    "詳細は以下を参照してください。\n",
    "\n",
    "- [真陽性、偽陽性、偽陰性、真陰性](https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative)\n",
    "- [正解度](https://developers.google.com/machine-learning/crash-course/classification/accuracy)\n",
    "- [適合率と再現率](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",
    "- [適合率-再現率と ROC 曲線の関係](https://www.biostat.wisc.edu/~page/rocpr.pdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FYdhSAoaF_TK"
   },
   "source": [
    "## ベースラインモデル"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IDbltVPg2m2q"
   },
   "source": [
    "### モデルを構築する\n",
    "\n",
    "次に、前に定義した関数を使用してモデルを作成し、トレーニングします。モデルはデフォルトよりも大きいバッチサイズ 2048 を使って適合されていることに注目してください。これは、各バッチに必ずいくつかの陽性サンプルが含まれるようにするために重要です。もし、バッチサイズが小さすぎると、学習できる不正取引が全くないという可能性があります。\n",
    "\n",
    "注意: このモデルはクラスの不均衡をうまく処理できません。後ほどこのチュートリアル内で改善します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:54.286462Z",
     "iopub.status.busy": "2022-12-14T23:05:54.285792Z",
     "iopub.status.idle": "2022-12-14T23:05:54.289934Z",
     "shell.execute_reply": "2022-12-14T23:05:54.289303Z"
    },
    "id": "ouUkwPcGQsy3"
   },
   "outputs": [],
   "source": [
    "EPOCHS = 100\n",
    "BATCH_SIZE = 2048\n",
    "\n",
    "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
    "    monitor='val_prc', \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": "2022-12-14T23:05:54.293358Z",
     "iopub.status.busy": "2022-12-14T23:05:54.292772Z",
     "iopub.status.idle": "2022-12-14T23:05:54.362051Z",
     "shell.execute_reply": "2022-12-14T23:05:54.361355Z"
    },
    "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\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trainable params: 497\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Non-trainable params: 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = make_model()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Wx7ND3_SqckO"
   },
   "source": [
    "モデルをテスト実行します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:54.367330Z",
     "iopub.status.busy": "2022-12-14T23:05:54.366697Z",
     "iopub.status.idle": "2022-12-14T23:05:54.853304Z",
     "shell.execute_reply": "2022-12-14T23:05:54.852550Z"
    },
    "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 433ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0.32376227],\n",
       "       [0.410775  ],\n",
       "       [0.78519666],\n",
       "       [0.8071737 ],\n",
       "       [0.24630985],\n",
       "       [0.43201268],\n",
       "       [0.14502314],\n",
       "       [0.4868623 ],\n",
       "       [0.392316  ],\n",
       "       [0.38101035]], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(train_features[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YKIgWqHms_03"
   },
   "source": [
    "### オプション: 正しい初期バイアスを設定する"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qk_3Ry6EoYDq"
   },
   "source": [
    "これら初期の推測はあまり良いとは言えません。データセットは不均衡であることが分かっています。それを反映できるように、出力レイヤーのバイアスを設定します。（参照: [ニューラルネットワークのトレーニングのレシピ: 「init well」](http://karpathy.github.io/2019/04/25/recipe/#2-set-up-the-end-to-end-trainingevaluation-skeleton--get-dumb-baselines)）これは初期収束に有用です。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PdbfWDuVpo6k"
   },
   "source": [
    "デフォルトのバイアス初期化では、損失は`math.log(2) = 0.69314`程度になります。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:54.857163Z",
     "iopub.status.busy": "2022-12-14T23:05:54.856590Z",
     "iopub.status.idle": "2022-12-14T23:05:55.666223Z",
     "shell.execute_reply": "2022-12-14T23:05:55.665558Z"
    },
    "id": "H-oPqh3SoGXk"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss: 0.5587\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": [
    "設定する正しいバイアスは、以下から導き出すことができます。\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": "2022-12-14T23:05:55.669994Z",
     "iopub.status.busy": "2022-12-14T23:05:55.669354Z",
     "iopub.status.idle": "2022-12-14T23:05:55.674240Z",
     "shell.execute_reply": "2022-12-14T23:05:55.673687Z"
    },
    "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": [
    "それを初期バイアスとして設定すると、モデルははるかに合理的な初期推測ができるようになります。\n",
    "\n",
    "これは`pos/total = 0.0018`に近い値になるはずです。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:55.677472Z",
     "iopub.status.busy": "2022-12-14T23:05:55.676907Z",
     "iopub.status.idle": "2022-12-14T23:05:55.784385Z",
     "shell.execute_reply": "2022-12-14T23:05:55.783683Z"
    },
    "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 45ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0.00103091],\n",
       "       [0.00088367],\n",
       "       [0.00175426],\n",
       "       [0.00091999],\n",
       "       [0.00124022],\n",
       "       [0.00087101],\n",
       "       [0.00024934],\n",
       "       [0.00167472],\n",
       "       [0.00049   ],\n",
       "       [0.00128492]], 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": [
    "この初期化では、初期損失はおおよそ次のようになります。\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": "2022-12-14T23:05:55.787801Z",
     "iopub.status.busy": "2022-12-14T23:05:55.787201Z",
     "iopub.status.idle": "2022-12-14T23:05:56.573409Z",
     "shell.execute_reply": "2022-12-14T23:05:56.572647Z"
    },
    "id": "xVDqCWXDqHSc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss: 0.0148\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": [
    "この初期の損失は、単純な初期化を行った場合の約 50 分の 1 です。\n",
    "\n",
    "この方法だと、陽性の例がないことを学習するだけのためにモデルが最初の数エポックを費やす必要がありません。また、これによって、トレーニング中の損失のプロットが読みやすくなります。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0EJj9ixKVBMT"
   },
   "source": [
    "### 初期の重みをチェックポイントする\n",
    "\n",
    "さまざまなトレーニングの実行を比較しやすくするために、この初期モデルの重みをチェックポイントファイルに保持し、トレーニングの前に各モデルにロードします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:56.577433Z",
     "iopub.status.busy": "2022-12-14T23:05:56.576756Z",
     "iopub.status.idle": "2022-12-14T23:05:56.612388Z",
     "shell.execute_reply": "2022-12-14T23:05:56.611787Z"
    },
    "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": [
    "### バイアス修正が有効であることを確認する\n",
    "\n",
    "先に進む前に、慎重なバイアス初期化が実際に役立ったかどうかを素早く確認します。\n",
    "\n",
    "この慎重な初期化を行った場合と行わなかった場合でモデルを 20 エポックトレーニングしてから損失を比較します。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:56.616093Z",
     "iopub.status.busy": "2022-12-14T23:05:56.615480Z",
     "iopub.status.idle": "2022-12-14T23:06:06.647340Z",
     "shell.execute_reply": "2022-12-14T23:06:06.646544Z"
    },
    "id": "Dm4-4K5RZ63Q"
   },
   "outputs": [],
   "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": "2022-12-14T23:06:06.651531Z",
     "iopub.status.busy": "2022-12-14T23:06:06.651017Z",
     "iopub.status.idle": "2022-12-14T23:06:16.729295Z",
     "shell.execute_reply": "2022-12-14T23:06:16.728514Z"
    },
    "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": "2022-12-14T23:06:16.733337Z",
     "iopub.status.busy": "2022-12-14T23:06:16.732707Z",
     "iopub.status.idle": "2022-12-14T23:06:16.737312Z",
     "shell.execute_reply": "2022-12-14T23:06:16.736696Z"
    },
    "id": "E3XsMBjhauFV"
   },
   "outputs": [],
   "source": [
    "def plot_loss(history, label, n):\n",
    "  # Use a log scale on y-axis 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')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:16.740400Z",
     "iopub.status.busy": "2022-12-14T23:06:16.739806Z",
     "iopub.status.idle": "2022-12-14T23:06:17.025527Z",
     "shell.execute_reply": "2022-12-14T23:06:17.024841Z"
    },
    "id": "dxFaskm7beC7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "上の図を見れば一目瞭然ですが、検証損失に関しては、この問題ではこのように慎重に初期化することによって、明確なアドバンテージを得ることができます。 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RsA_7SEntRaV"
   },
   "source": [
    "### モデルをトレーニングする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:17.029214Z",
     "iopub.status.busy": "2022-12-14T23:06:17.028697Z",
     "iopub.status.idle": "2022-12-14T23:06:42.186885Z",
     "shell.execute_reply": "2022-12-14T23:06:42.186165Z"
    },
    "id": "yZKAc8NCDnoR"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 2:01 - loss: 0.0117 - tp: 50.0000 - fp: 7.0000 - tn: 47538.0000 - fn: 22.0000 - accuracy: 0.9994 - precision: 0.8772 - recall: 0.6944 - auc: 0.9020 - prc: 0.7246"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0106 - tp: 50.0000 - fp: 19.0000 - tn: 72073.0000 - fn: 51.0000 - accuracy: 0.9990 - precision: 0.7246 - recall: 0.4950 - auc: 0.8369 - 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\r",
      "26/90 [=======>......................] - ETA: 0s - loss: 0.0148 - tp: 54.0000 - fp: 27.0000 - tn: 98624.0000 - fn: 112.0000 - accuracy: 0.9986 - precision: 0.6667 - recall: 0.3253 - auc: 0.7691 - prc: 0.3432"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0137 - tp: 61.0000 - fp: 35.0000 - tn: 125194.0000 - fn: 151.0000 - accuracy: 0.9985 - precision: 0.6354 - recall: 0.2877 - auc: 0.7550 - prc: 0.3022"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0135 - tp: 73.0000 - fp: 39.0000 - tn: 151751.0000 - fn: 202.0000 - accuracy: 0.9984 - precision: 0.6518 - recall: 0.2655 - auc: 0.7613 - prc: 0.2927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0124 - tp: 85.0000 - fp: 44.0000 - tn: 178324.0000 - fn: 236.0000 - accuracy: 0.9984 - precision: 0.6589 - recall: 0.2648 - auc: 0.7723 - prc: 0.3013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0114 - tp: 93.0000 - fp: 46.0000 - tn: 204910.0000 - fn: 264.0000 - accuracy: 0.9985 - precision: 0.6691 - recall: 0.2605 - auc: 0.7846 - prc: 0.3099"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 [==============================] - 2s 11ms/step - loss: 0.0109 - tp: 106.0000 - fp: 56.0000 - tn: 227398.0000 - fn: 285.0000 - accuracy: 0.9985 - precision: 0.6543 - recall: 0.2711 - auc: 0.7874 - prc: 0.3099 - val_loss: 0.0056 - val_tp: 20.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 49.0000 - val_accuracy: 0.9988 - val_precision: 0.8333 - val_recall: 0.2899 - val_auc: 0.8831 - val_prc: 0.6267\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0050 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.3333 - auc: 0.9910 - prc: 0.5471"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 16.0000 - fp: 3.0000 - tn: 28621.0000 - fn: 32.0000 - accuracy: 0.9988 - precision: 0.8421 - recall: 0.3333 - auc: 0.9110 - prc: 0.4808 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0062 - tp: 31.0000 - fp: 9.0000 - tn: 55198.0000 - fn: 58.0000 - accuracy: 0.9988 - precision: 0.7750 - recall: 0.3483 - auc: 0.9052 - 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\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0063 - tp: 59.0000 - fp: 9.0000 - tn: 83815.0000 - fn: 85.0000 - accuracy: 0.9989 - precision: 0.8676 - recall: 0.4097 - auc: 0.8875 - 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\b\b\r",
      "54/90 [=================>............] - ETA: 0s - loss: 0.0070 - tp: 74.0000 - fp: 12.0000 - tn: 110381.0000 - fn: 125.0000 - accuracy: 0.9988 - precision: 0.8605 - recall: 0.3719 - auc: 0.8717 - prc: 0.5017"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071 - tp: 97.0000 - fp: 17.0000 - tn: 134905.0000 - fn: 149.0000 - accuracy: 0.9988 - precision: 0.8509 - recall: 0.3943 - auc: 0.8668 - prc: 0.4993"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 - tp: 112.0000 - fp: 23.0000 - tn: 157394.0000 - fn: 167.0000 - accuracy: 0.9988 - precision: 0.8296 - recall: 0.4014 - auc: 0.8567 - prc: 0.4817"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073 - tp: 126.0000 - fp: 27.0000 - tn: 181923.0000 - fn: 196.0000 - accuracy: 0.9988 - precision: 0.8235 - recall: 0.3913 - auc: 0.8536 - prc: 0.4774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073 - tp: 126.0000 - fp: 27.0000 - tn: 181927.0000 - fn: 196.0000 - accuracy: 0.9988 - precision: 0.8235 - recall: 0.3913 - auc: 0.8536 - prc: 0.4774 - val_loss: 0.0048 - val_tp: 29.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 40.0000 - val_accuracy: 0.9989 - val_precision: 0.7838 - val_recall: 0.4203 - val_auc: 0.8837 - val_prc: 0.6447\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0011 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2048.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - 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\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0069 - tp: 19.0000 - fp: 4.0000 - tn: 28622.0000 - fn: 27.0000 - accuracy: 0.9989 - precision: 0.8261 - recall: 0.4130 - auc: 0.8110 - prc: 0.4759                         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0063 - tp: 44.0000 - fp: 8.0000 - tn: 55196.0000 - fn: 48.0000 - accuracy: 0.9990 - precision: 0.8462 - recall: 0.4783 - auc: 0.8499 - prc: 0.5731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0061 - tp: 69.0000 - fp: 11.0000 - tn: 81769.0000 - fn: 71.0000 - accuracy: 0.9990 - precision: 0.8625 - recall: 0.4929 - auc: 0.8794 - prc: 0.5989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0062 - tp: 93.0000 - fp: 16.0000 - tn: 108337.0000 - fn: 98.0000 - accuracy: 0.9989 - precision: 0.8532 - recall: 0.4869 - auc: 0.8742 - prc: 0.6012"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0062 - tp: 123.0000 - fp: 18.0000 - tn: 134907.0000 - fn: 120.0000 - accuracy: 0.9990 - precision: 0.8723 - recall: 0.5062 - auc: 0.8780 - 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",
      "80/90 [=========================>....] - ETA: 0s - loss: 0.0062 - tp: 149.0000 - fp: 20.0000 - tn: 163526.0000 - fn: 145.0000 - accuracy: 0.9990 - precision: 0.8817 - recall: 0.5068 - auc: 0.8783 - prc: 0.6130"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0061 - tp: 163.0000 - fp: 22.0000 - tn: 181932.0000 - fn: 159.0000 - accuracy: 0.9990 - precision: 0.8811 - recall: 0.5062 - auc: 0.8777 - prc: 0.6132 - val_loss: 0.0044 - val_tp: 34.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 35.0000 - val_accuracy: 0.9991 - val_precision: 0.8095 - val_recall: 0.4928 - val_auc: 0.8838 - val_prc: 0.6321\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0103 - tp: 3.0000 - fp: 1.0000 - tn: 2041.0000 - fn: 3.0000 - accuracy: 0.9980 - precision: 0.7500 - recall: 0.5000 - auc: 0.8309 - prc: 0.6325"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 31.0000 - fp: 4.0000 - tn: 28616.0000 - fn: 21.0000 - accuracy: 0.9991 - precision: 0.8857 - recall: 0.5962 - auc: 0.9023 - prc: 0.7162"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 49.0000 - fp: 7.0000 - tn: 55195.0000 - fn: 45.0000 - accuracy: 0.9991 - precision: 0.8750 - recall: 0.5213 - auc: 0.8811 - prc: 0.6535"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0055 - tp: 71.0000 - fp: 14.0000 - tn: 81766.0000 - fn: 69.0000 - accuracy: 0.9990 - precision: 0.8353 - recall: 0.5071 - auc: 0.8947 - prc: 0.6442"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0057 - tp: 92.0000 - fp: 17.0000 - tn: 108337.0000 - fn: 98.0000 - accuracy: 0.9989 - precision: 0.8440 - recall: 0.4842 - auc: 0.8929 - prc: 0.6349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 118.0000 - fp: 24.0000 - tn: 134911.0000 - fn: 115.0000 - accuracy: 0.9990 - precision: 0.8310 - recall: 0.5064 - auc: 0.8952 - 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\b\b\b\b\r",
      "80/90 [=========================>....] - ETA: 0s - loss: 0.0056 - tp: 144.0000 - fp: 29.0000 - tn: 163526.0000 - fn: 141.0000 - accuracy: 0.9990 - precision: 0.8324 - recall: 0.5053 - auc: 0.9019 - prc: 0.6415"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0058 - tp: 158.0000 - fp: 33.0000 - tn: 181921.0000 - fn: 164.0000 - accuracy: 0.9989 - precision: 0.8272 - recall: 0.4907 - auc: 0.8958 - prc: 0.6258 - val_loss: 0.0042 - val_tp: 41.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 28.0000 - val_accuracy: 0.9992 - val_precision: 0.8367 - val_recall: 0.5942 - val_auc: 0.8910 - val_prc: 0.6413\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0064 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.5000 - auc: 0.9156 - prc: 0.8352"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 31.0000 - fp: 4.0000 - tn: 28609.0000 - fn: 28.0000 - accuracy: 0.9989 - precision: 0.8857 - recall: 0.5254 - auc: 0.9392 - prc: 0.7050 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0060 - tp: 55.0000 - fp: 9.0000 - tn: 57222.0000 - fn: 58.0000 - accuracy: 0.9988 - precision: 0.8594 - recall: 0.4867 - auc: 0.9186 - 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",
      "42/90 [=============>................] - ETA: 0s - loss: 0.0051 - tp: 81.0000 - fp: 14.0000 - tn: 85851.0000 - fn: 70.0000 - accuracy: 0.9990 - precision: 0.8526 - recall: 0.5364 - auc: 0.9290 - 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\r",
      "56/90 [=================>............] - ETA: 0s - loss: 0.0051 - tp: 107.0000 - fp: 21.0000 - tn: 114473.0000 - fn: 87.0000 - accuracy: 0.9991 - precision: 0.8359 - recall: 0.5515 - auc: 0.9238 - 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\r",
      "70/90 [======================>.......] - ETA: 0s - loss: 0.0055 - tp: 133.0000 - fp: 28.0000 - tn: 143082.0000 - fn: 117.0000 - accuracy: 0.9990 - precision: 0.8261 - recall: 0.5320 - auc: 0.9125 - prc: 0.6386"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - ETA: 0s - loss: 0.0055 - tp: 160.0000 - fp: 33.0000 - tn: 171695.0000 - fn: 144.0000 - accuracy: 0.9990 - precision: 0.8290 - recall: 0.5263 - auc: 0.9081 - prc: 0.6419"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 170.0000 - fp: 36.0000 - tn: 181918.0000 - fn: 152.0000 - accuracy: 0.9990 - precision: 0.8252 - recall: 0.5280 - auc: 0.9085 - prc: 0.6395 - val_loss: 0.0040 - val_tp: 42.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 27.0000 - val_accuracy: 0.9992 - val_precision: 0.8400 - val_recall: 0.6087 - val_auc: 0.8983 - val_prc: 0.6740\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0026 - tp: 2.0000 - fp: 1.0000 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.6667 - recall: 0.6667 - auc: 0.9997 - prc: 0.7690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 32.0000 - fp: 2.0000 - tn: 28615.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.9412 - recall: 0.5818 - auc: 0.9262 - prc: 0.7382"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 63.0000 - fp: 5.0000 - tn: 55179.0000 - fn: 49.0000 - accuracy: 0.9990 - precision: 0.9265 - recall: 0.5625 - auc: 0.9185 - prc: 0.7274"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0052 - tp: 91.0000 - fp: 9.0000 - tn: 83790.0000 - fn: 78.0000 - accuracy: 0.9990 - precision: 0.9100 - recall: 0.5385 - auc: 0.9071 - prc: 0.7100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0047 - tp: 113.0000 - fp: 14.0000 - tn: 112417.0000 - fn: 96.0000 - accuracy: 0.9990 - precision: 0.8898 - recall: 0.5407 - auc: 0.9151 - prc: 0.7103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 135.0000 - fp: 23.0000 - tn: 141035.0000 - fn: 119.0000 - accuracy: 0.9990 - precision: 0.8544 - recall: 0.5315 - auc: 0.9141 - 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",
      "83/90 [==========================>...] - ETA: 0s - loss: 0.0052 - tp: 164.0000 - fp: 29.0000 - tn: 169649.0000 - fn: 142.0000 - accuracy: 0.9990 - precision: 0.8497 - recall: 0.5359 - auc: 0.9105 - prc: 0.6607"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0053 - tp: 172.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8473 - recall: 0.5342 - auc: 0.9071 - prc: 0.6464 - val_loss: 0.0039 - val_tp: 42.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 27.0000 - val_accuracy: 0.9992 - val_precision: 0.8400 - val_recall: 0.6087 - val_auc: 0.8982 - val_prc: 0.6779\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0031 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.7500 - auc: 0.9991 - prc: 0.8372"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0059 - tp: 34.0000 - fp: 8.0000 - tn: 28608.0000 - fn: 22.0000 - accuracy: 0.9990 - precision: 0.8095 - recall: 0.6071 - auc: 0.9362 - prc: 0.6302 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0052 - tp: 59.0000 - fp: 10.0000 - tn: 57231.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.8551 - recall: 0.5728 - auc: 0.9260 - prc: 0.6603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0052 - tp: 88.0000 - fp: 14.0000 - tn: 85844.0000 - fn: 70.0000 - accuracy: 0.9990 - precision: 0.8627 - recall: 0.5570 - auc: 0.9198 - prc: 0.6748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 114.0000 - fp: 22.0000 - tn: 114461.0000 - fn: 91.0000 - accuracy: 0.9990 - precision: 0.8382 - recall: 0.5561 - auc: 0.9233 - 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\r",
      "70/90 [======================>.......] - ETA: 0s - loss: 0.0050 - tp: 141.0000 - fp: 27.0000 - tn: 143083.0000 - fn: 109.0000 - accuracy: 0.9991 - precision: 0.8393 - recall: 0.5640 - auc: 0.9189 - prc: 0.6652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 164.0000 - fp: 30.0000 - tn: 169655.0000 - fn: 135.0000 - accuracy: 0.9990 - precision: 0.8454 - recall: 0.5485 - auc: 0.9153 - 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 [==============================] - 0s 5ms/step - loss: 0.0051 - tp: 172.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 150.0000 - accuracy: 0.9990 - precision: 0.8473 - recall: 0.5342 - auc: 0.9135 - prc: 0.6628 - val_loss: 0.0038 - val_tp: 46.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 23.0000 - val_accuracy: 0.9993 - val_precision: 0.8519 - val_recall: 0.6667 - val_auc: 0.8982 - val_prc: 0.6813\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0029 - tp: 1.0000 - fp: 1.0000 - tn: 2043.0000 - fn: 3.0000 - accuracy: 0.9980 - precision: 0.5000 - recall: 0.2500 - auc: 0.9996 - prc: 0.7709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 25.0000 - fp: 7.0000 - tn: 28615.0000 - fn: 25.0000 - accuracy: 0.9989 - precision: 0.7812 - recall: 0.5000 - auc: 0.9091 - 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\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0051 - tp: 50.0000 - fp: 12.0000 - tn: 55194.0000 - fn: 40.0000 - accuracy: 0.9991 - precision: 0.8065 - recall: 0.5556 - auc: 0.9045 - prc: 0.6065"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0054 - tp: 72.0000 - fp: 14.0000 - tn: 81768.0000 - fn: 66.0000 - accuracy: 0.9990 - precision: 0.8372 - recall: 0.5217 - auc: 0.9010 - prc: 0.6066"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0052 - tp: 108.0000 - fp: 17.0000 - tn: 108329.0000 - fn: 90.0000 - accuracy: 0.9990 - precision: 0.8640 - recall: 0.5455 - auc: 0.9131 - prc: 0.6619"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 129.0000 - fp: 21.0000 - tn: 134912.0000 - fn: 106.0000 - accuracy: 0.9991 - precision: 0.8600 - recall: 0.5489 - auc: 0.9117 - prc: 0.6673"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 148.0000 - fp: 24.0000 - tn: 161487.0000 - fn: 133.0000 - accuracy: 0.9990 - precision: 0.8605 - recall: 0.5267 - auc: 0.9118 - 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 5ms/step - loss: 0.0054 - tp: 171.0000 - fp: 28.0000 - tn: 181926.0000 - fn: 151.0000 - accuracy: 0.9990 - precision: 0.8593 - recall: 0.5311 - auc: 0.9073 - prc: 0.6439 - val_loss: 0.0037 - val_tp: 46.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 23.0000 - val_accuracy: 0.9993 - val_precision: 0.8519 - val_recall: 0.6667 - val_auc: 0.8981 - val_prc: 0.6888\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 8.8972e-04 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2045.0000 - 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: 0.0032 - tp: 26.0000 - fp: 5.0000 - tn: 28621.0000 - fn: 20.0000 - accuracy: 0.9991 - precision: 0.8387 - recall: 0.5652 - auc: 0.9670 - prc: 0.8315         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 66.0000 - fp: 11.0000 - tn: 55182.0000 - fn: 37.0000 - accuracy: 0.9991 - precision: 0.8571 - recall: 0.6408 - auc: 0.9557 - prc: 0.7457"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 89.0000 - fp: 16.0000 - tn: 83809.0000 - fn: 54.0000 - accuracy: 0.9992 - precision: 0.8476 - recall: 0.6224 - auc: 0.9433 - prc: 0.7201"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 117.0000 - fp: 21.0000 - tn: 110384.0000 - fn: 70.0000 - accuracy: 0.9992 - precision: 0.8478 - recall: 0.6257 - auc: 0.9430 - prc: 0.7060"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 139.0000 - fp: 23.0000 - tn: 136950.0000 - fn: 104.0000 - accuracy: 0.9991 - precision: 0.8580 - recall: 0.5720 - auc: 0.9250 - prc: 0.6797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 164.0000 - fp: 28.0000 - tn: 165567.0000 - fn: 129.0000 - accuracy: 0.9991 - precision: 0.8542 - recall: 0.5597 - auc: 0.9171 - prc: 0.6691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 179.0000 - fp: 33.0000 - tn: 181921.0000 - fn: 143.0000 - accuracy: 0.9990 - precision: 0.8443 - recall: 0.5559 - auc: 0.9167 - prc: 0.6665 - val_loss: 0.0036 - val_tp: 46.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 23.0000 - val_accuracy: 0.9993 - val_precision: 0.8519 - val_recall: 0.6667 - val_auc: 0.8981 - val_prc: 0.7000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0124 - tp: 2.0000 - fp: 2.0000 - tn: 2043.0000 - fn: 1.0000 - accuracy: 0.9985 - precision: 0.5000 - recall: 0.6667 - auc: 0.8315 - prc: 0.3099"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 22.0000 - fp: 6.0000 - tn: 28630.0000 - fn: 14.0000 - accuracy: 0.9993 - precision: 0.7857 - recall: 0.6111 - auc: 0.9296 - prc: 0.6164"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 48.0000 - fp: 9.0000 - tn: 55197.0000 - fn: 42.0000 - accuracy: 0.9991 - precision: 0.8421 - recall: 0.5333 - auc: 0.9157 - prc: 0.6562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 71.0000 - fp: 17.0000 - tn: 81768.0000 - fn: 64.0000 - accuracy: 0.9990 - precision: 0.8068 - recall: 0.5259 - auc: 0.9325 - prc: 0.6755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 97.0000 - fp: 22.0000 - tn: 108345.0000 - fn: 80.0000 - accuracy: 0.9991 - precision: 0.8151 - recall: 0.5480 - auc: 0.9370 - prc: 0.6842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 129.0000 - fp: 24.0000 - tn: 134913.0000 - fn: 102.0000 - accuracy: 0.9991 - precision: 0.8431 - recall: 0.5584 - auc: 0.9298 - 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\r",
      "79/90 [=========================>....] - ETA: 0s - loss: 0.0045 - tp: 153.0000 - fp: 26.0000 - tn: 161489.0000 - fn: 124.0000 - accuracy: 0.9991 - precision: 0.8547 - recall: 0.5523 - auc: 0.9251 - prc: 0.6902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0048 - tp: 171.0000 - fp: 28.0000 - tn: 181926.0000 - fn: 151.0000 - accuracy: 0.9990 - precision: 0.8593 - recall: 0.5311 - auc: 0.9151 - prc: 0.6786 - val_loss: 0.0036 - val_tp: 48.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 21.0000 - val_accuracy: 0.9993 - val_precision: 0.8421 - val_recall: 0.6957 - val_auc: 0.9053 - val_prc: 0.7026\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 5.8868e-04 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2048.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - 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\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0049 - tp: 21.0000 - fp: 4.0000 - tn: 28627.0000 - fn: 20.0000 - accuracy: 0.9992 - precision: 0.8400 - recall: 0.5122 - auc: 0.8890 - 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: 0.0050 - tp: 47.0000 - fp: 8.0000 - tn: 55204.0000 - fn: 37.0000 - accuracy: 0.9992 - precision: 0.8545 - recall: 0.5595 - auc: 0.9155 - prc: 0.6210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 79.0000 - fp: 11.0000 - tn: 81773.0000 - fn: 57.0000 - accuracy: 0.9992 - precision: 0.8778 - recall: 0.5809 - auc: 0.9143 - 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\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0049 - tp: 110.0000 - fp: 16.0000 - tn: 108342.0000 - fn: 76.0000 - accuracy: 0.9992 - precision: 0.8730 - recall: 0.5914 - auc: 0.9210 - prc: 0.6617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 138.0000 - fp: 20.0000 - tn: 134914.0000 - fn: 96.0000 - accuracy: 0.9991 - precision: 0.8734 - recall: 0.5897 - auc: 0.9221 - prc: 0.6628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 158.0000 - fp: 25.0000 - tn: 161483.0000 - fn: 126.0000 - accuracy: 0.9991 - precision: 0.8634 - recall: 0.5563 - auc: 0.9127 - prc: 0.6553"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0051 - tp: 178.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 144.0000 - accuracy: 0.9991 - precision: 0.8599 - recall: 0.5528 - auc: 0.9104 - prc: 0.6587 - val_loss: 0.0034 - val_tp: 47.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 22.0000 - val_accuracy: 0.9993 - val_precision: 0.8545 - val_recall: 0.6812 - val_auc: 0.9053 - val_prc: 0.7099\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0061 - 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: 0.7840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0062 - tp: 22.0000 - fp: 7.0000 - tn: 28617.0000 - fn: 26.0000 - accuracy: 0.9988 - precision: 0.7586 - recall: 0.4583 - auc: 0.8738 - prc: 0.5585 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0056 - tp: 56.0000 - fp: 11.0000 - tn: 55184.0000 - fn: 45.0000 - accuracy: 0.9990 - precision: 0.8358 - recall: 0.5545 - auc: 0.8949 - prc: 0.6368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0057 - tp: 87.0000 - fp: 16.0000 - tn: 81751.0000 - fn: 66.0000 - accuracy: 0.9990 - precision: 0.8447 - recall: 0.5686 - auc: 0.9009 - prc: 0.6489"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 107.0000 - fp: 21.0000 - tn: 110380.0000 - fn: 84.0000 - accuracy: 0.9991 - precision: 0.8359 - recall: 0.5602 - auc: 0.8994 - prc: 0.6286"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0052 - tp: 139.0000 - fp: 25.0000 - tn: 138990.0000 - fn: 110.0000 - accuracy: 0.9990 - precision: 0.8476 - recall: 0.5582 - auc: 0.9127 - prc: 0.6541"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0049 - tp: 163.0000 - fp: 29.0000 - tn: 167616.0000 - fn: 128.0000 - accuracy: 0.9991 - precision: 0.8490 - recall: 0.5601 - auc: 0.9183 - 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\b\b\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0050 - tp: 179.0000 - fp: 33.0000 - tn: 181921.0000 - fn: 143.0000 - accuracy: 0.9990 - precision: 0.8443 - recall: 0.5559 - auc: 0.9214 - prc: 0.6630 - val_loss: 0.0034 - val_tp: 47.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 22.0000 - val_accuracy: 0.9993 - val_precision: 0.8545 - val_recall: 0.6812 - val_auc: 0.9053 - val_prc: 0.7207\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0023 - tp: 2.0000 - fp: 1.0000 - tn: 2043.0000 - fn: 2.0000 - accuracy: 0.9985 - precision: 0.6667 - recall: 0.5000 - auc: 0.9998 - prc: 0.8723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 22.0000 - fp: 8.0000 - tn: 28623.0000 - fn: 19.0000 - accuracy: 0.9991 - precision: 0.7333 - recall: 0.5366 - auc: 0.9502 - prc: 0.6459"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0034 - tp: 42.0000 - fp: 11.0000 - tn: 55211.0000 - fn: 32.0000 - accuracy: 0.9992 - precision: 0.7925 - recall: 0.5676 - auc: 0.9451 - 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\b\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0043 - tp: 61.0000 - fp: 15.0000 - tn: 81787.0000 - fn: 57.0000 - accuracy: 0.9991 - precision: 0.8026 - recall: 0.5169 - auc: 0.9099 - prc: 0.6217"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 96.0000 - fp: 20.0000 - tn: 108354.0000 - fn: 74.0000 - accuracy: 0.9991 - precision: 0.8276 - recall: 0.5647 - auc: 0.9226 - prc: 0.6620"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 130.0000 - fp: 22.0000 - tn: 136968.0000 - fn: 96.0000 - accuracy: 0.9991 - precision: 0.8553 - recall: 0.5752 - auc: 0.9239 - prc: 0.6844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 158.0000 - fp: 27.0000 - tn: 165577.0000 - fn: 126.0000 - accuracy: 0.9991 - precision: 0.8541 - recall: 0.5563 - auc: 0.9234 - prc: 0.6739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0048 - tp: 177.0000 - fp: 27.0000 - tn: 181927.0000 - fn: 145.0000 - accuracy: 0.9991 - precision: 0.8676 - recall: 0.5497 - auc: 0.9136 - prc: 0.6684 - val_loss: 0.0033 - val_tp: 49.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8596 - val_recall: 0.7101 - val_auc: 0.9126 - val_prc: 0.7302\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0073 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.5000 - auc: 0.8323 - prc: 0.6701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 31.0000 - fp: 5.0000 - tn: 30658.0000 - fn: 26.0000 - accuracy: 0.9990 - precision: 0.8611 - recall: 0.5439 - auc: 0.9026 - prc: 0.7040 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 59.0000 - fp: 8.0000 - tn: 59281.0000 - fn: 44.0000 - accuracy: 0.9991 - precision: 0.8806 - recall: 0.5728 - auc: 0.9262 - prc: 0.7421"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 99.0000 - fp: 15.0000 - tn: 87878.0000 - fn: 72.0000 - accuracy: 0.9990 - precision: 0.8684 - recall: 0.5789 - auc: 0.9230 - prc: 0.7298"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 128.0000 - fp: 24.0000 - tn: 116492.0000 - fn: 92.0000 - accuracy: 0.9990 - precision: 0.8421 - recall: 0.5818 - auc: 0.9286 - prc: 0.7049"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0046 - tp: 151.0000 - fp: 28.0000 - tn: 145114.0000 - fn: 115.0000 - accuracy: 0.9990 - precision: 0.8436 - recall: 0.5677 - auc: 0.9276 - prc: 0.6984"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0047 - tp: 176.0000 - fp: 35.0000 - tn: 173733.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8341 - recall: 0.5641 - auc: 0.9237 - prc: 0.6829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 183.0000 - fp: 36.0000 - tn: 181918.0000 - fn: 139.0000 - accuracy: 0.9990 - precision: 0.8356 - recall: 0.5683 - auc: 0.9245 - prc: 0.6851 - val_loss: 0.0033 - val_tp: 49.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8596 - val_recall: 0.7101 - val_auc: 0.9126 - val_prc: 0.7323\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0031 - 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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0054 - tp: 28.0000 - fp: 10.0000 - tn: 30661.0000 - fn: 21.0000 - accuracy: 0.9990 - precision: 0.7368 - recall: 0.5714 - auc: 0.8966 - prc: 0.6005"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 55.0000 - fp: 13.0000 - tn: 59281.0000 - fn: 43.0000 - accuracy: 0.9991 - precision: 0.8088 - recall: 0.5612 - auc: 0.9174 - prc: 0.6666"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 86.0000 - fp: 17.0000 - tn: 87904.0000 - fn: 57.0000 - accuracy: 0.9992 - precision: 0.8350 - recall: 0.6014 - auc: 0.9362 - prc: 0.7092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 127.0000 - fp: 20.0000 - tn: 116512.0000 - fn: 77.0000 - accuracy: 0.9992 - precision: 0.8639 - recall: 0.6225 - auc: 0.9477 - prc: 0.7403"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0041 - tp: 154.0000 - fp: 21.0000 - tn: 145128.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.8800 - recall: 0.5946 - auc: 0.9393 - prc: 0.7408"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 184.0000 - fp: 29.0000 - tn: 173742.0000 - fn: 125.0000 - accuracy: 0.9991 - precision: 0.8638 - recall: 0.5955 - auc: 0.9344 - prc: 0.7228"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 192.0000 - fp: 30.0000 - tn: 181924.0000 - fn: 130.0000 - accuracy: 0.9991 - precision: 0.8649 - recall: 0.5963 - auc: 0.9324 - prc: 0.7217 - val_loss: 0.0033 - val_tp: 49.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8448 - val_recall: 0.7101 - val_auc: 0.9125 - val_prc: 0.7339\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0022 - tp: 2.0000 - fp: 1.0000 - tn: 2045.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.6667 - recall: 1.0000 - auc: 0.9998 - prc: 0.7973"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 32.0000 - fp: 6.0000 - tn: 28618.0000 - fn: 16.0000 - accuracy: 0.9992 - precision: 0.8421 - recall: 0.6667 - auc: 0.9155 - 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\r",
      "28/90 [========>.....................] - ETA: 0s - loss: 0.0042 - tp: 63.0000 - fp: 8.0000 - tn: 57239.0000 - fn: 34.0000 - accuracy: 0.9993 - precision: 0.8873 - recall: 0.6495 - auc: 0.9114 - prc: 0.6734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 90.0000 - fp: 13.0000 - tn: 85856.0000 - fn: 57.0000 - accuracy: 0.9992 - precision: 0.8738 - recall: 0.6122 - auc: 0.9209 - prc: 0.6893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 122.0000 - fp: 20.0000 - tn: 114469.0000 - fn: 77.0000 - accuracy: 0.9992 - precision: 0.8592 - recall: 0.6131 - auc: 0.9238 - prc: 0.6924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 144.0000 - fp: 25.0000 - tn: 143085.0000 - fn: 106.0000 - accuracy: 0.9991 - precision: 0.8521 - recall: 0.5760 - auc: 0.9191 - prc: 0.6755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 174.0000 - fp: 31.0000 - tn: 169658.0000 - fn: 121.0000 - accuracy: 0.9991 - precision: 0.8488 - recall: 0.5898 - auc: 0.9228 - prc: 0.6834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 190.0000 - fp: 34.0000 - tn: 181920.0000 - fn: 132.0000 - accuracy: 0.9991 - precision: 0.8482 - recall: 0.5901 - auc: 0.9199 - prc: 0.6823 - val_loss: 0.0032 - 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: 0.9126 - val_prc: 0.7428\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0041 - tp: 2.0000 - fp: 1.0000 - tn: 2045.0000 - fn: 0.0000e+00 - accuracy: 0.9995 - precision: 0.6667 - recall: 1.0000 - auc: 0.9995 - prc: 0.4507"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 - tp: 29.0000 - fp: 7.0000 - tn: 28607.0000 - fn: 29.0000 - accuracy: 0.9987 - precision: 0.8056 - recall: 0.5000 - auc: 0.8608 - prc: 0.5239 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0053 - tp: 56.0000 - fp: 11.0000 - tn: 57230.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8358 - recall: 0.5437 - auc: 0.8920 - prc: 0.6223"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0049 - tp: 92.0000 - fp: 19.0000 - tn: 85843.0000 - fn: 62.0000 - accuracy: 0.9991 - precision: 0.8288 - recall: 0.5974 - auc: 0.9112 - prc: 0.6549"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0049 - tp: 116.0000 - fp: 24.0000 - tn: 112415.0000 - fn: 85.0000 - accuracy: 0.9990 - precision: 0.8286 - recall: 0.5771 - auc: 0.9143 - 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\r",
      "69/90 [======================>.......] - ETA: 0s - loss: 0.0049 - tp: 145.0000 - fp: 27.0000 - tn: 141027.0000 - fn: 113.0000 - accuracy: 0.9990 - precision: 0.8430 - recall: 0.5620 - auc: 0.9137 - prc: 0.6567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 170.0000 - fp: 30.0000 - tn: 167607.0000 - fn: 129.0000 - accuracy: 0.9991 - precision: 0.8500 - recall: 0.5686 - auc: 0.9120 - prc: 0.6660"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 185.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 137.0000 - accuracy: 0.9991 - precision: 0.8565 - recall: 0.5745 - auc: 0.9136 - prc: 0.6757 - val_loss: 0.0032 - val_tp: 49.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8909 - val_recall: 0.7101 - val_auc: 0.9126 - val_prc: 0.7463\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0018 - 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: 0.0042 - tp: 25.0000 - fp: 5.0000 - tn: 28621.0000 - fn: 21.0000 - accuracy: 0.9991 - precision: 0.8333 - recall: 0.5435 - auc: 0.9339 - prc: 0.6700 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 52.0000 - fp: 8.0000 - tn: 55196.0000 - fn: 40.0000 - accuracy: 0.9991 - precision: 0.8667 - recall: 0.5652 - auc: 0.9285 - prc: 0.7064"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 75.0000 - fp: 13.0000 - tn: 81772.0000 - fn: 60.0000 - accuracy: 0.9991 - precision: 0.8523 - recall: 0.5556 - auc: 0.9213 - prc: 0.6789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 102.0000 - fp: 18.0000 - tn: 108345.0000 - fn: 79.0000 - accuracy: 0.9991 - precision: 0.8500 - recall: 0.5635 - auc: 0.9217 - prc: 0.6790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 140.0000 - fp: 22.0000 - tn: 134908.0000 - fn: 98.0000 - accuracy: 0.9991 - precision: 0.8642 - recall: 0.5882 - auc: 0.9235 - prc: 0.7100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 165.0000 - fp: 31.0000 - tn: 161481.0000 - fn: 115.0000 - accuracy: 0.9991 - precision: 0.8418 - recall: 0.5893 - auc: 0.9205 - prc: 0.6935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 186.0000 - fp: 34.0000 - tn: 181920.0000 - fn: 136.0000 - accuracy: 0.9991 - precision: 0.8455 - recall: 0.5776 - auc: 0.9198 - prc: 0.6871 - val_loss: 0.0032 - val_tp: 49.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 20.0000 - val_accuracy: 0.9994 - val_precision: 0.8909 - val_recall: 0.7101 - val_auc: 0.9126 - val_prc: 0.7495\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 7.3119e-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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0047 - tp: 21.0000 - fp: 6.0000 - tn: 30663.0000 - fn: 30.0000 - accuracy: 0.9988 - precision: 0.7778 - recall: 0.4118 - auc: 0.9303 - prc: 0.6382         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 59.0000 - fp: 15.0000 - tn: 59268.0000 - fn: 50.0000 - accuracy: 0.9989 - precision: 0.7973 - recall: 0.5413 - auc: 0.9349 - prc: 0.6933"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 90.0000 - fp: 20.0000 - tn: 85835.0000 - fn: 71.0000 - accuracy: 0.9989 - precision: 0.8182 - recall: 0.5590 - auc: 0.9278 - prc: 0.6997"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0047 - tp: 106.0000 - fp: 25.0000 - tn: 112413.0000 - fn: 96.0000 - accuracy: 0.9989 - precision: 0.8092 - recall: 0.5248 - auc: 0.9273 - prc: 0.6725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 134.0000 - fp: 28.0000 - tn: 141032.0000 - fn: 118.0000 - accuracy: 0.9990 - precision: 0.8272 - recall: 0.5317 - auc: 0.9297 - prc: 0.6899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 163.0000 - fp: 33.0000 - tn: 167604.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8316 - recall: 0.5452 - auc: 0.9256 - 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\b\b\b\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0045 - tp: 179.0000 - fp: 37.0000 - tn: 181917.0000 - fn: 143.0000 - accuracy: 0.9990 - precision: 0.8287 - recall: 0.5559 - auc: 0.9246 - prc: 0.6875 - val_loss: 0.0032 - val_tp: 50.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 19.0000 - val_accuracy: 0.9994 - val_precision: 0.8621 - val_recall: 0.7246 - val_auc: 0.9198 - val_prc: 0.7475\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0037 - tp: 2.0000 - fp: 1.0000 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9990 - precision: 0.6667 - recall: 0.6667 - auc: 0.9992 - prc: 0.7778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 7.0000 - tn: 28618.0000 - fn: 10.0000 - accuracy: 0.9994 - precision: 0.8409 - recall: 0.7872 - auc: 0.9248 - prc: 0.7390"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 65.0000 - fp: 11.0000 - tn: 55188.0000 - fn: 32.0000 - accuracy: 0.9992 - precision: 0.8553 - recall: 0.6701 - auc: 0.9375 - prc: 0.7443"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 92.0000 - fp: 15.0000 - tn: 81767.0000 - fn: 46.0000 - accuracy: 0.9993 - precision: 0.8598 - recall: 0.6667 - auc: 0.9377 - prc: 0.7161"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 120.0000 - fp: 19.0000 - tn: 110377.0000 - fn: 76.0000 - accuracy: 0.9991 - precision: 0.8633 - recall: 0.6122 - auc: 0.9278 - 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\b\r",
      "67/90 [=====================>........] - ETA: 0s - loss: 0.0043 - tp: 147.0000 - fp: 24.0000 - tn: 136952.0000 - fn: 93.0000 - accuracy: 0.9991 - precision: 0.8596 - recall: 0.6125 - auc: 0.9263 - prc: 0.6921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 178.0000 - fp: 29.0000 - tn: 165559.0000 - fn: 122.0000 - accuracy: 0.9991 - precision: 0.8599 - recall: 0.5933 - auc: 0.9225 - prc: 0.6935"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 188.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8584 - recall: 0.5839 - auc: 0.9231 - prc: 0.6918 - val_loss: 0.0031 - val_tp: 50.0000 - val_fp: 6.0000 - val_tn: 45494.0000 - val_fn: 19.0000 - val_accuracy: 0.9995 - val_precision: 0.8929 - val_recall: 0.7246 - val_auc: 0.9198 - val_prc: 0.7588\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0079 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.5000 - auc: 0.7476 - prc: 0.5027"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 31.0000 - fp: 2.0000 - tn: 28615.0000 - fn: 24.0000 - accuracy: 0.9991 - precision: 0.9394 - recall: 0.5636 - auc: 0.9355 - prc: 0.7191 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 62.0000 - fp: 9.0000 - tn: 55181.0000 - fn: 44.0000 - accuracy: 0.9990 - precision: 0.8732 - recall: 0.5849 - auc: 0.9236 - 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\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0047 - tp: 89.0000 - fp: 12.0000 - tn: 83805.0000 - fn: 62.0000 - accuracy: 0.9991 - precision: 0.8812 - recall: 0.5894 - auc: 0.9195 - prc: 0.6742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 118.0000 - fp: 17.0000 - tn: 112423.0000 - fn: 82.0000 - accuracy: 0.9991 - precision: 0.8741 - recall: 0.5900 - auc: 0.9266 - prc: 0.6948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 147.0000 - fp: 20.0000 - tn: 138994.0000 - fn: 103.0000 - accuracy: 0.9991 - precision: 0.8802 - recall: 0.5880 - auc: 0.9271 - prc: 0.7145"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 175.0000 - fp: 25.0000 - tn: 167616.0000 - fn: 120.0000 - accuracy: 0.9991 - precision: 0.8750 - recall: 0.5932 - auc: 0.9263 - prc: 0.7068"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 195.0000 - fp: 30.0000 - tn: 181924.0000 - fn: 127.0000 - accuracy: 0.9991 - precision: 0.8667 - recall: 0.6056 - auc: 0.9308 - prc: 0.7085 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7603\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0013 - 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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0041 - tp: 26.0000 - fp: 5.0000 - tn: 30667.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8387 - recall: 0.5417 - auc: 0.9366 - prc: 0.6814                     "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 59.0000 - fp: 15.0000 - tn: 59276.0000 - fn: 42.0000 - accuracy: 0.9990 - precision: 0.7973 - recall: 0.5842 - auc: 0.9297 - prc: 0.6541"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 87.0000 - fp: 17.0000 - tn: 87893.0000 - fn: 67.0000 - accuracy: 0.9990 - precision: 0.8365 - recall: 0.5649 - auc: 0.9211 - prc: 0.6668"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 115.0000 - fp: 18.0000 - tn: 116509.0000 - fn: 94.0000 - accuracy: 0.9990 - precision: 0.8647 - recall: 0.5502 - auc: 0.9081 - 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",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0047 - tp: 149.0000 - fp: 22.0000 - tn: 145118.0000 - fn: 119.0000 - accuracy: 0.9990 - precision: 0.8713 - recall: 0.5560 - auc: 0.9095 - prc: 0.6839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 172.0000 - fp: 26.0000 - tn: 173748.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8687 - recall: 0.5621 - auc: 0.9158 - prc: 0.6850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 185.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 137.0000 - accuracy: 0.9991 - precision: 0.8645 - recall: 0.5745 - auc: 0.9200 - prc: 0.6928 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.8793 - val_recall: 0.7391 - val_auc: 0.9198 - val_prc: 0.7615\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 23/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0156 - tp: 2.0000 - fp: 1.0000 - tn: 2040.0000 - fn: 5.0000 - accuracy: 0.9971 - precision: 0.6667 - recall: 0.2857 - auc: 0.7827 - prc: 0.3871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 29.0000 - fp: 4.0000 - tn: 28623.0000 - fn: 16.0000 - accuracy: 0.9993 - precision: 0.8788 - recall: 0.6444 - auc: 0.9325 - prc: 0.7469"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 57.0000 - fp: 12.0000 - tn: 59291.0000 - fn: 32.0000 - accuracy: 0.9993 - precision: 0.8261 - recall: 0.6404 - auc: 0.9205 - prc: 0.7074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 79.0000 - fp: 15.0000 - tn: 87910.0000 - fn: 60.0000 - accuracy: 0.9991 - precision: 0.8404 - recall: 0.5683 - auc: 0.9271 - prc: 0.7017"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 107.0000 - fp: 19.0000 - tn: 116525.0000 - fn: 85.0000 - accuracy: 0.9991 - precision: 0.8492 - recall: 0.5573 - auc: 0.9209 - 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\r",
      "70/90 [======================>.......] - ETA: 0s - loss: 0.0041 - tp: 137.0000 - fp: 26.0000 - tn: 143093.0000 - fn: 104.0000 - accuracy: 0.9991 - precision: 0.8405 - recall: 0.5685 - auc: 0.9244 - prc: 0.7019"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - ETA: 0s - loss: 0.0041 - tp: 177.0000 - fp: 30.0000 - tn: 171701.0000 - fn: 124.0000 - accuracy: 0.9991 - precision: 0.8551 - recall: 0.5880 - auc: 0.9277 - prc: 0.7239"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 191.0000 - fp: 34.0000 - tn: 181920.0000 - fn: 131.0000 - accuracy: 0.9991 - precision: 0.8489 - recall: 0.5932 - auc: 0.9277 - prc: 0.7225 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7642\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0141 - tp: 4.0000 - fp: 1.0000 - tn: 2037.0000 - fn: 6.0000 - accuracy: 0.9966 - precision: 0.8000 - recall: 0.4000 - auc: 0.8483 - 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\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0051 - tp: 28.0000 - fp: 8.0000 - tn: 30652.0000 - fn: 32.0000 - accuracy: 0.9987 - precision: 0.7778 - recall: 0.4667 - auc: 0.9239 - prc: 0.6802"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 53.0000 - fp: 10.0000 - tn: 59280.0000 - fn: 49.0000 - accuracy: 0.9990 - precision: 0.8413 - recall: 0.5196 - auc: 0.9057 - prc: 0.6861"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0047 - tp: 93.0000 - fp: 14.0000 - tn: 87885.0000 - fn: 72.0000 - accuracy: 0.9990 - precision: 0.8692 - recall: 0.5636 - auc: 0.9171 - prc: 0.7053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 119.0000 - fp: 20.0000 - tn: 116505.0000 - fn: 92.0000 - accuracy: 0.9990 - precision: 0.8561 - recall: 0.5640 - auc: 0.9231 - prc: 0.7075"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0042 - tp: 151.0000 - fp: 24.0000 - tn: 145123.0000 - fn: 110.0000 - accuracy: 0.9991 - precision: 0.8629 - recall: 0.5785 - auc: 0.9301 - prc: 0.7267"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 183.0000 - fp: 28.0000 - tn: 173741.0000 - fn: 128.0000 - accuracy: 0.9991 - precision: 0.8673 - recall: 0.5884 - auc: 0.9332 - prc: 0.7298"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 188.0000 - fp: 28.0000 - tn: 181926.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8704 - recall: 0.5839 - auc: 0.9323 - prc: 0.7307 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.8793 - val_recall: 0.7391 - val_auc: 0.9199 - val_prc: 0.7626\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0076 - tp: 1.0000 - fp: 2.0000 - tn: 2043.0000 - fn: 2.0000 - accuracy: 0.9980 - precision: 0.3333 - recall: 0.3333 - auc: 0.9992 - prc: 0.4284"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 31.0000 - fp: 9.0000 - tn: 30653.0000 - fn: 27.0000 - accuracy: 0.9988 - precision: 0.7750 - recall: 0.5345 - auc: 0.9301 - prc: 0.6859"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 57.0000 - fp: 14.0000 - tn: 57234.0000 - fn: 39.0000 - accuracy: 0.9991 - precision: 0.8028 - recall: 0.5938 - auc: 0.9367 - prc: 0.7227"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 91.0000 - fp: 17.0000 - tn: 85848.0000 - fn: 60.0000 - accuracy: 0.9991 - precision: 0.8426 - recall: 0.6026 - auc: 0.9264 - prc: 0.7440"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 124.0000 - fp: 22.0000 - tn: 112422.0000 - fn: 72.0000 - accuracy: 0.9992 - precision: 0.8493 - recall: 0.6327 - auc: 0.9355 - prc: 0.7419"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 158.0000 - fp: 26.0000 - tn: 141040.0000 - fn: 88.0000 - accuracy: 0.9992 - precision: 0.8587 - recall: 0.6423 - auc: 0.9383 - prc: 0.7407"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 185.0000 - fp: 34.0000 - tn: 167602.0000 - fn: 115.0000 - accuracy: 0.9991 - precision: 0.8447 - recall: 0.6167 - auc: 0.9275 - prc: 0.7143"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 197.0000 - fp: 36.0000 - tn: 181918.0000 - fn: 125.0000 - accuracy: 0.9991 - precision: 0.8455 - recall: 0.6118 - auc: 0.9246 - prc: 0.7086 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7728\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 26/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0047 - tp: 5.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.8333 - auc: 0.9163 - 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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0035 - tp: 46.0000 - fp: 3.0000 - tn: 30653.0000 - fn: 18.0000 - accuracy: 0.9993 - precision: 0.9388 - recall: 0.7188 - auc: 0.9525 - prc: 0.8049 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 68.0000 - fp: 7.0000 - tn: 57228.0000 - fn: 41.0000 - accuracy: 0.9992 - precision: 0.9067 - recall: 0.6239 - auc: 0.9303 - prc: 0.7431"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 101.0000 - fp: 13.0000 - tn: 85846.0000 - fn: 56.0000 - accuracy: 0.9992 - precision: 0.8860 - recall: 0.6433 - auc: 0.9258 - prc: 0.7212"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 127.0000 - fp: 19.0000 - tn: 112414.0000 - fn: 80.0000 - accuracy: 0.9991 - precision: 0.8699 - recall: 0.6135 - auc: 0.9218 - 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\b\b\b\r",
      "68/90 [=====================>........] - ETA: 0s - loss: 0.0044 - tp: 152.0000 - fp: 26.0000 - tn: 138983.0000 - fn: 103.0000 - accuracy: 0.9991 - precision: 0.8539 - recall: 0.5961 - auc: 0.9246 - prc: 0.7056"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 177.0000 - fp: 31.0000 - tn: 167606.0000 - fn: 122.0000 - accuracy: 0.9991 - precision: 0.8510 - recall: 0.5920 - auc: 0.9305 - prc: 0.7103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 191.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 131.0000 - accuracy: 0.9991 - precision: 0.8604 - recall: 0.5932 - auc: 0.9292 - prc: 0.7152 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7744\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 27/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.6983e-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: 0.0038 - tp: 27.0000 - fp: 9.0000 - tn: 28621.0000 - fn: 15.0000 - accuracy: 0.9992 - precision: 0.7500 - recall: 0.6429 - auc: 0.9158 - prc: 0.6970         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 62.0000 - fp: 11.0000 - tn: 57231.0000 - fn: 40.0000 - accuracy: 0.9991 - precision: 0.8493 - recall: 0.6078 - auc: 0.9159 - prc: 0.7337"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 92.0000 - fp: 16.0000 - tn: 83796.0000 - fn: 64.0000 - accuracy: 0.9990 - precision: 0.8519 - recall: 0.5897 - auc: 0.9190 - prc: 0.7102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 129.0000 - fp: 21.0000 - tn: 110366.0000 - fn: 76.0000 - accuracy: 0.9991 - precision: 0.8600 - recall: 0.6293 - auc: 0.9236 - prc: 0.7322"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 149.0000 - fp: 26.0000 - tn: 136950.0000 - fn: 91.0000 - accuracy: 0.9991 - precision: 0.8514 - recall: 0.6208 - auc: 0.9263 - prc: 0.7233"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 188.0000 - fp: 31.0000 - tn: 165557.0000 - fn: 112.0000 - accuracy: 0.9991 - precision: 0.8584 - recall: 0.6267 - auc: 0.9275 - prc: 0.7266"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 202.0000 - fp: 33.0000 - tn: 181921.0000 - fn: 120.0000 - accuracy: 0.9992 - precision: 0.8596 - recall: 0.6273 - auc: 0.9262 - prc: 0.7209 - val_loss: 0.0031 - 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: 0.9198 - val_prc: 0.7687\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0063 - tp: 2.0000 - fp: 2.0000 - tn: 2042.0000 - fn: 2.0000 - accuracy: 0.9980 - precision: 0.5000 - recall: 0.5000 - auc: 0.9991 - prc: 0.4598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0049 - tp: 25.0000 - fp: 8.0000 - tn: 28620.0000 - fn: 19.0000 - accuracy: 0.9991 - precision: 0.7576 - recall: 0.5682 - auc: 0.9077 - prc: 0.5816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 58.0000 - fp: 11.0000 - tn: 55192.0000 - fn: 35.0000 - accuracy: 0.9992 - precision: 0.8406 - recall: 0.6237 - auc: 0.9238 - prc: 0.7100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 96.0000 - fp: 17.0000 - tn: 81756.0000 - fn: 51.0000 - accuracy: 0.9992 - precision: 0.8496 - recall: 0.6531 - auc: 0.9312 - prc: 0.7393"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 129.0000 - fp: 22.0000 - tn: 108332.0000 - fn: 61.0000 - accuracy: 0.9992 - precision: 0.8543 - recall: 0.6789 - auc: 0.9387 - prc: 0.7477"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 164.0000 - fp: 28.0000 - tn: 134895.0000 - fn: 81.0000 - accuracy: 0.9992 - precision: 0.8542 - recall: 0.6694 - auc: 0.9380 - prc: 0.7562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 195.0000 - fp: 33.0000 - tn: 161468.0000 - fn: 96.0000 - accuracy: 0.9992 - precision: 0.8553 - recall: 0.6701 - auc: 0.9374 - prc: 0.7542"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 213.0000 - fp: 37.0000 - tn: 181917.0000 - fn: 109.0000 - accuracy: 0.9992 - precision: 0.8520 - recall: 0.6615 - auc: 0.9356 - prc: 0.7422 - val_loss: 0.0031 - 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: 0.9127 - val_prc: 0.7715\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 29/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0100 - tp: 4.0000 - fp: 1.0000 - tn: 2040.0000 - fn: 3.0000 - accuracy: 0.9980 - precision: 0.8000 - recall: 0.5714 - auc: 0.8557 - 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\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0039 - tp: 27.0000 - fp: 5.0000 - tn: 28621.0000 - fn: 19.0000 - accuracy: 0.9992 - precision: 0.8438 - recall: 0.5870 - auc: 0.9121 - prc: 0.7200"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 47.0000 - fp: 10.0000 - tn: 55195.0000 - fn: 44.0000 - accuracy: 0.9990 - precision: 0.8246 - recall: 0.5165 - auc: 0.8891 - prc: 0.6422"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 65.0000 - fp: 11.0000 - tn: 81777.0000 - fn: 67.0000 - accuracy: 0.9990 - precision: 0.8553 - recall: 0.4924 - auc: 0.8891 - prc: 0.6418"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 93.0000 - fp: 13.0000 - tn: 108353.0000 - fn: 85.0000 - accuracy: 0.9991 - precision: 0.8774 - recall: 0.5225 - auc: 0.9064 - prc: 0.6916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 125.0000 - fp: 21.0000 - tn: 134917.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.8562 - recall: 0.5435 - auc: 0.9165 - prc: 0.6987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 161.0000 - fp: 24.0000 - tn: 161488.0000 - fn: 119.0000 - accuracy: 0.9991 - precision: 0.8703 - recall: 0.5750 - auc: 0.9170 - prc: 0.7097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 183.0000 - fp: 30.0000 - tn: 181924.0000 - fn: 139.0000 - accuracy: 0.9991 - precision: 0.8592 - recall: 0.5683 - auc: 0.9214 - prc: 0.7053 - val_loss: 0.0031 - val_tp: 47.0000 - val_fp: 3.0000 - val_tn: 45497.0000 - val_fn: 22.0000 - val_accuracy: 0.9995 - val_precision: 0.9400 - val_recall: 0.6812 - val_auc: 0.9127 - val_prc: 0.7746\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 30/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.0832e-04 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2048.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - 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\b\b\b\b\b\b\b\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.0042 - tp: 24.0000 - fp: 3.0000 - tn: 28623.0000 - fn: 22.0000 - accuracy: 0.9991 - precision: 0.8889 - recall: 0.5217 - auc: 0.8904 - prc: 0.6842                             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 60.0000 - fp: 9.0000 - tn: 57237.0000 - fn: 38.0000 - accuracy: 0.9992 - precision: 0.8696 - recall: 0.6122 - auc: 0.9177 - prc: 0.7404"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 83.0000 - fp: 13.0000 - tn: 85857.0000 - fn: 63.0000 - accuracy: 0.9991 - precision: 0.8646 - recall: 0.5685 - auc: 0.9066 - prc: 0.6869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 107.0000 - fp: 16.0000 - tn: 112434.0000 - fn: 83.0000 - accuracy: 0.9991 - precision: 0.8699 - recall: 0.5632 - auc: 0.9175 - prc: 0.7039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 132.0000 - fp: 23.0000 - tn: 141048.0000 - fn: 109.0000 - accuracy: 0.9991 - precision: 0.8516 - recall: 0.5477 - auc: 0.9182 - prc: 0.6904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 165.0000 - fp: 28.0000 - tn: 169655.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8549 - recall: 0.5482 - auc: 0.9143 - prc: 0.6808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 179.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 143.0000 - accuracy: 0.9991 - precision: 0.8606 - recall: 0.5559 - auc: 0.9167 - prc: 0.6924 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7745\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 31/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0015 - 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: 0.0042 - tp: 34.0000 - fp: 4.0000 - tn: 28616.0000 - fn: 18.0000 - accuracy: 0.9992 - precision: 0.8947 - recall: 0.6538 - auc: 0.9223 - prc: 0.7453 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 72.0000 - fp: 9.0000 - tn: 57231.0000 - fn: 32.0000 - accuracy: 0.9993 - precision: 0.8889 - recall: 0.6923 - auc: 0.9368 - prc: 0.7745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 107.0000 - fp: 14.0000 - tn: 85842.0000 - fn: 53.0000 - accuracy: 0.9992 - precision: 0.8843 - recall: 0.6687 - auc: 0.9368 - prc: 0.7630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 136.0000 - fp: 19.0000 - tn: 112409.0000 - fn: 76.0000 - accuracy: 0.9992 - precision: 0.8774 - recall: 0.6415 - auc: 0.9332 - prc: 0.7484"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 163.0000 - fp: 23.0000 - tn: 141028.0000 - fn: 98.0000 - accuracy: 0.9991 - precision: 0.8763 - recall: 0.6245 - auc: 0.9302 - prc: 0.7396"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 193.0000 - fp: 26.0000 - tn: 169652.0000 - fn: 113.0000 - accuracy: 0.9992 - precision: 0.8813 - recall: 0.6307 - auc: 0.9355 - prc: 0.7565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 199.0000 - fp: 28.0000 - tn: 181926.0000 - fn: 123.0000 - accuracy: 0.9992 - precision: 0.8767 - recall: 0.6180 - auc: 0.9293 - prc: 0.7386 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7777\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 32/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 5.5394e-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: 0.0046 - tp: 33.0000 - fp: 4.0000 - tn: 28612.0000 - fn: 23.0000 - accuracy: 0.9991 - precision: 0.8919 - recall: 0.5893 - auc: 0.9185 - prc: 0.6992         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 57.0000 - fp: 12.0000 - tn: 55183.0000 - fn: 44.0000 - accuracy: 0.9990 - precision: 0.8261 - recall: 0.5644 - auc: 0.9048 - 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\r",
      "41/90 [============>.................] - ETA: 0s - loss: 0.0045 - tp: 84.0000 - fp: 17.0000 - tn: 83802.0000 - fn: 65.0000 - accuracy: 0.9990 - precision: 0.8317 - recall: 0.5638 - auc: 0.9151 - prc: 0.6784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 110.0000 - fp: 22.0000 - tn: 112421.0000 - fn: 87.0000 - accuracy: 0.9990 - precision: 0.8333 - recall: 0.5584 - auc: 0.9101 - prc: 0.6498"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 143.0000 - fp: 26.0000 - tn: 141035.0000 - fn: 108.0000 - accuracy: 0.9991 - precision: 0.8462 - recall: 0.5697 - auc: 0.9114 - 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",
      "83/90 [==========================>...] - ETA: 0s - loss: 0.0045 - tp: 173.0000 - fp: 29.0000 - tn: 169650.0000 - fn: 132.0000 - accuracy: 0.9991 - precision: 0.8564 - recall: 0.5672 - auc: 0.9154 - prc: 0.6862"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 186.0000 - fp: 32.0000 - tn: 181922.0000 - fn: 136.0000 - accuracy: 0.9991 - precision: 0.8532 - recall: 0.5776 - auc: 0.9152 - prc: 0.6856 - val_loss: 0.0031 - 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: 0.9126 - val_prc: 0.7653\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 7.3895e-04 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2048.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - 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\b\b\b\b\b\b\b\b\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0047 - tp: 27.0000 - fp: 1.0000 - tn: 30673.0000 - fn: 19.0000 - accuracy: 0.9993 - precision: 0.9643 - recall: 0.5870 - auc: 0.8682 - prc: 0.6305                             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 67.0000 - fp: 4.0000 - tn: 59287.0000 - fn: 34.0000 - accuracy: 0.9994 - precision: 0.9437 - recall: 0.6634 - auc: 0.9148 - prc: 0.7141"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 107.0000 - fp: 8.0000 - tn: 87896.0000 - fn: 53.0000 - accuracy: 0.9993 - precision: 0.9304 - recall: 0.6687 - auc: 0.9273 - prc: 0.7379"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 137.0000 - fp: 14.0000 - tn: 116512.0000 - fn: 73.0000 - accuracy: 0.9993 - precision: 0.9073 - recall: 0.6524 - auc: 0.9325 - prc: 0.7414"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0040 - tp: 171.0000 - fp: 19.0000 - tn: 145125.0000 - fn: 93.0000 - accuracy: 0.9992 - precision: 0.9000 - recall: 0.6477 - auc: 0.9310 - prc: 0.7382"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 196.0000 - fp: 28.0000 - tn: 173748.0000 - fn: 108.0000 - accuracy: 0.9992 - precision: 0.8750 - recall: 0.6447 - auc: 0.9285 - prc: 0.7187"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 205.0000 - fp: 30.0000 - tn: 181924.0000 - fn: 117.0000 - accuracy: 0.9992 - precision: 0.8723 - recall: 0.6366 - auc: 0.9262 - prc: 0.7156 - val_loss: 0.0031 - val_tp: 46.0000 - val_fp: 3.0000 - val_tn: 45497.0000 - val_fn: 23.0000 - val_accuracy: 0.9994 - val_precision: 0.9388 - val_recall: 0.6667 - val_auc: 0.9127 - val_prc: 0.7731\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 34/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 3.6070e-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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0033 - tp: 30.0000 - fp: 6.0000 - tn: 30666.0000 - fn: 18.0000 - accuracy: 0.9992 - precision: 0.8333 - recall: 0.6250 - auc: 0.9682 - prc: 0.7407         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 59.0000 - fp: 9.0000 - tn: 59284.0000 - fn: 40.0000 - accuracy: 0.9992 - precision: 0.8676 - recall: 0.5960 - auc: 0.9386 - prc: 0.7112"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0044 - tp: 90.0000 - fp: 13.0000 - tn: 87891.0000 - fn: 70.0000 - accuracy: 0.9991 - precision: 0.8738 - recall: 0.5625 - auc: 0.9273 - prc: 0.7054"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 118.0000 - fp: 16.0000 - tn: 116515.0000 - fn: 87.0000 - accuracy: 0.9991 - precision: 0.8806 - recall: 0.5756 - auc: 0.9235 - prc: 0.6982"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0041 - tp: 145.0000 - fp: 21.0000 - tn: 145137.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.8735 - recall: 0.5800 - auc: 0.9291 - prc: 0.7003"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 184.0000 - fp: 25.0000 - tn: 173749.0000 - fn: 122.0000 - accuracy: 0.9992 - precision: 0.8804 - recall: 0.6013 - auc: 0.9322 - prc: 0.7238"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 194.0000 - fp: 27.0000 - tn: 181927.0000 - fn: 128.0000 - accuracy: 0.9991 - precision: 0.8778 - recall: 0.6025 - auc: 0.9308 - prc: 0.7248 - val_loss: 0.0031 - val_tp: 49.0000 - val_fp: 3.0000 - val_tn: 45497.0000 - val_fn: 20.0000 - val_accuracy: 0.9995 - val_precision: 0.9423 - val_recall: 0.7101 - val_auc: 0.9127 - val_prc: 0.7761\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 35/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.0639e-04 - tp: 0.0000e+00 - fp: 0.0000e+00 - tn: 2048.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - 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\b\b\b\b\b\b\b\b\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0043 - tp: 30.0000 - fp: 5.0000 - tn: 30657.0000 - fn: 28.0000 - accuracy: 0.9989 - precision: 0.8571 - recall: 0.5172 - auc: 0.9475 - prc: 0.7516                             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 53.0000 - fp: 13.0000 - tn: 59282.0000 - fn: 44.0000 - accuracy: 0.9990 - precision: 0.8030 - recall: 0.5464 - auc: 0.9269 - 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\r",
      "43/90 [=============>................] - ETA: 0s - loss: 0.0047 - tp: 76.0000 - fp: 26.0000 - tn: 87891.0000 - fn: 71.0000 - accuracy: 0.9989 - precision: 0.7451 - recall: 0.5170 - auc: 0.9276 - prc: 0.6241"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0045 - tp: 102.0000 - fp: 31.0000 - tn: 116508.0000 - fn: 95.0000 - accuracy: 0.9989 - precision: 0.7669 - recall: 0.5178 - auc: 0.9331 - prc: 0.6555"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0042 - tp: 134.0000 - fp: 32.0000 - tn: 145126.0000 - fn: 116.0000 - accuracy: 0.9990 - precision: 0.8072 - recall: 0.5360 - auc: 0.9352 - prc: 0.6909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 169.0000 - fp: 34.0000 - tn: 173741.0000 - fn: 136.0000 - accuracy: 0.9990 - precision: 0.8325 - recall: 0.5541 - auc: 0.9336 - prc: 0.7068"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 178.0000 - fp: 35.0000 - tn: 181919.0000 - fn: 144.0000 - accuracy: 0.9990 - precision: 0.8357 - recall: 0.5528 - auc: 0.9308 - prc: 0.7084 - val_loss: 0.0031 - 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: 0.9126 - val_prc: 0.7680\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 36/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0041 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2043.0000 - fn: 3.0000 - accuracy: 0.9985 - precision: 1.0000 - recall: 0.4000 - auc: 0.9997 - prc: 0.8614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 31.0000 - fp: 7.0000 - tn: 28611.0000 - fn: 23.0000 - accuracy: 0.9990 - precision: 0.8158 - recall: 0.5741 - auc: 0.8971 - prc: 0.6137 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 66.0000 - fp: 13.0000 - tn: 55176.0000 - fn: 41.0000 - accuracy: 0.9990 - precision: 0.8354 - recall: 0.6168 - auc: 0.9149 - 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\r",
      "40/90 [============>.................] - ETA: 0s - loss: 0.0044 - tp: 95.0000 - fp: 14.0000 - tn: 81757.0000 - fn: 54.0000 - accuracy: 0.9992 - precision: 0.8716 - recall: 0.6376 - auc: 0.9186 - 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\b\r",
      "53/90 [================>.............] - ETA: 0s - loss: 0.0042 - tp: 125.0000 - fp: 18.0000 - tn: 108329.0000 - fn: 72.0000 - accuracy: 0.9992 - precision: 0.8741 - recall: 0.6345 - auc: 0.9255 - prc: 0.7215"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 150.0000 - fp: 19.0000 - tn: 134909.0000 - fn: 90.0000 - accuracy: 0.9992 - precision: 0.8876 - recall: 0.6250 - auc: 0.9283 - prc: 0.7291"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 176.0000 - fp: 26.0000 - tn: 161483.0000 - fn: 107.0000 - accuracy: 0.9992 - precision: 0.8713 - recall: 0.6219 - auc: 0.9267 - prc: 0.7224"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 197.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 125.0000 - accuracy: 0.9992 - precision: 0.8717 - recall: 0.6118 - auc: 0.9261 - prc: 0.7202 - val_loss: 0.0031 - 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: 0.9199 - val_prc: 0.7784\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 37/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0032 - tp: 1.0000 - fp: 0.0000e+00 - tn: 2046.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.5000 - auc: 0.7477 - prc: 0.5014"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 30.0000 - fp: 5.0000 - tn: 28614.0000 - fn: 23.0000 - accuracy: 0.9990 - precision: 0.8571 - recall: 0.5660 - auc: 0.9047 - prc: 0.7317 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0047 - tp: 53.0000 - fp: 11.0000 - tn: 57232.0000 - fn: 48.0000 - accuracy: 0.9990 - precision: 0.8281 - recall: 0.5248 - auc: 0.9048 - prc: 0.6749"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 83.0000 - fp: 20.0000 - tn: 85842.0000 - fn: 71.0000 - accuracy: 0.9989 - precision: 0.8058 - recall: 0.5390 - auc: 0.9112 - prc: 0.6800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 117.0000 - fp: 28.0000 - tn: 114454.0000 - fn: 89.0000 - accuracy: 0.9990 - precision: 0.8069 - recall: 0.5680 - auc: 0.9189 - prc: 0.7026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 144.0000 - fp: 29.0000 - tn: 143082.0000 - fn: 105.0000 - accuracy: 0.9991 - precision: 0.8324 - recall: 0.5783 - auc: 0.9227 - prc: 0.7224"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 170.0000 - fp: 34.0000 - tn: 169657.0000 - fn: 123.0000 - accuracy: 0.9991 - precision: 0.8333 - recall: 0.5802 - auc: 0.9188 - 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\b\b\b\b\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0041 - tp: 188.0000 - fp: 36.0000 - tn: 181918.0000 - fn: 134.0000 - accuracy: 0.9991 - precision: 0.8393 - recall: 0.5839 - auc: 0.9230 - prc: 0.7139 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8500 - val_recall: 0.7391 - val_auc: 0.9126 - val_prc: 0.7760\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 38/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0016 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.6667 - 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: 0.0027 - tp: 36.0000 - fp: 6.0000 - tn: 28618.0000 - fn: 12.0000 - accuracy: 0.9994 - precision: 0.8571 - recall: 0.7500 - auc: 0.9682 - prc: 0.8093 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 66.0000 - fp: 10.0000 - tn: 55186.0000 - fn: 34.0000 - accuracy: 0.9992 - precision: 0.8684 - recall: 0.6600 - auc: 0.9191 - prc: 0.7264"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0035 - tp: 90.0000 - fp: 14.0000 - tn: 81764.0000 - fn: 52.0000 - accuracy: 0.9992 - precision: 0.8654 - recall: 0.6338 - auc: 0.9323 - prc: 0.7540"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0036 - tp: 120.0000 - fp: 16.0000 - tn: 108334.0000 - fn: 74.0000 - accuracy: 0.9992 - precision: 0.8824 - recall: 0.6186 - auc: 0.9322 - prc: 0.7531"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 150.0000 - fp: 21.0000 - tn: 134907.0000 - fn: 90.0000 - accuracy: 0.9992 - precision: 0.8772 - recall: 0.6250 - auc: 0.9283 - prc: 0.7462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0037 - tp: 184.0000 - fp: 26.0000 - tn: 161481.0000 - fn: 101.0000 - accuracy: 0.9992 - precision: 0.8762 - recall: 0.6456 - auc: 0.9308 - prc: 0.7479"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 202.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 120.0000 - accuracy: 0.9992 - precision: 0.8745 - recall: 0.6273 - auc: 0.9246 - prc: 0.7336 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8500 - val_recall: 0.7391 - val_auc: 0.9126 - val_prc: 0.7762\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 39/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0111 - tp: 2.0000 - fp: 4.0000 - tn: 2041.0000 - fn: 1.0000 - accuracy: 0.9976 - precision: 0.3333 - recall: 0.6667 - auc: 0.8312 - prc: 0.3665"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0054 - tp: 36.0000 - fp: 7.0000 - tn: 30650.0000 - fn: 27.0000 - accuracy: 0.9989 - precision: 0.8372 - recall: 0.5714 - auc: 0.9117 - prc: 0.6884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 74.0000 - fp: 9.0000 - tn: 59266.0000 - fn: 43.0000 - accuracy: 0.9991 - precision: 0.8916 - recall: 0.6325 - auc: 0.9351 - prc: 0.7808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 102.0000 - fp: 16.0000 - tn: 85840.0000 - fn: 58.0000 - accuracy: 0.9991 - precision: 0.8644 - recall: 0.6375 - auc: 0.9242 - prc: 0.7451"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 127.0000 - fp: 23.0000 - tn: 114459.0000 - fn: 79.0000 - accuracy: 0.9991 - precision: 0.8467 - recall: 0.6165 - auc: 0.9238 - prc: 0.7296"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 161.0000 - fp: 31.0000 - tn: 141020.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8385 - recall: 0.6169 - auc: 0.9263 - prc: 0.7379"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 185.0000 - fp: 35.0000 - tn: 167602.0000 - fn: 114.0000 - accuracy: 0.9991 - precision: 0.8409 - recall: 0.6187 - auc: 0.9255 - prc: 0.7332"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 204.0000 - fp: 39.0000 - tn: 181915.0000 - fn: 118.0000 - accuracy: 0.9991 - precision: 0.8395 - recall: 0.6335 - auc: 0.9292 - prc: 0.7404 - val_loss: 0.0031 - val_tp: 48.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 21.0000 - val_accuracy: 0.9995 - val_precision: 0.9231 - val_recall: 0.6957 - val_auc: 0.9127 - val_prc: 0.7799\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 40/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0038 - tp: 4.0000 - fp: 0.0000e+00 - tn: 2042.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.6667 - auc: 0.9995 - prc: 0.9149"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 34.0000 - fp: 7.0000 - tn: 28613.0000 - fn: 18.0000 - accuracy: 0.9991 - precision: 0.8293 - recall: 0.6538 - auc: 0.9416 - prc: 0.7618 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 59.0000 - fp: 11.0000 - tn: 57228.0000 - fn: 46.0000 - accuracy: 0.9990 - precision: 0.8429 - recall: 0.5619 - auc: 0.9517 - prc: 0.7618"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 89.0000 - fp: 16.0000 - tn: 83795.0000 - fn: 68.0000 - accuracy: 0.9990 - precision: 0.8476 - recall: 0.5669 - auc: 0.9355 - prc: 0.7439"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 119.0000 - fp: 23.0000 - tn: 112414.0000 - fn: 84.0000 - accuracy: 0.9991 - precision: 0.8380 - recall: 0.5862 - auc: 0.9327 - prc: 0.7266"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 148.0000 - fp: 26.0000 - tn: 141034.0000 - fn: 104.0000 - accuracy: 0.9991 - precision: 0.8506 - recall: 0.5873 - auc: 0.9317 - prc: 0.7279"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 180.0000 - fp: 29.0000 - tn: 169656.0000 - fn: 119.0000 - accuracy: 0.9991 - precision: 0.8612 - recall: 0.6020 - auc: 0.9339 - prc: 0.7390"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 192.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 130.0000 - accuracy: 0.9991 - precision: 0.8688 - recall: 0.5963 - auc: 0.9324 - prc: 0.7400 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8500 - val_recall: 0.7391 - val_auc: 0.9127 - val_prc: 0.7764\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 41/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0050 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2045.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.6667 - auc: 0.8327 - prc: 0.6686"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 33.0000 - fp: 7.0000 - tn: 30664.0000 - fn: 16.0000 - accuracy: 0.9993 - precision: 0.8250 - recall: 0.6735 - auc: 0.9275 - prc: 0.6442 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 67.0000 - fp: 13.0000 - tn: 59273.0000 - fn: 39.0000 - accuracy: 0.9991 - precision: 0.8375 - recall: 0.6321 - auc: 0.9379 - prc: 0.7313"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 91.0000 - fp: 17.0000 - tn: 87892.0000 - fn: 64.0000 - accuracy: 0.9991 - precision: 0.8426 - recall: 0.5871 - auc: 0.9346 - prc: 0.7180"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 119.0000 - fp: 20.0000 - tn: 114469.0000 - fn: 80.0000 - accuracy: 0.9991 - precision: 0.8561 - recall: 0.5980 - auc: 0.9288 - prc: 0.7273"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 153.0000 - fp: 24.0000 - tn: 143083.0000 - fn: 100.0000 - accuracy: 0.9991 - precision: 0.8644 - recall: 0.6047 - auc: 0.9260 - prc: 0.7349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - ETA: 0s - loss: 0.0039 - tp: 188.0000 - fp: 29.0000 - tn: 171696.0000 - fn: 119.0000 - accuracy: 0.9991 - precision: 0.8664 - recall: 0.6124 - auc: 0.9259 - prc: 0.7298"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 198.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 124.0000 - accuracy: 0.9991 - precision: 0.8646 - recall: 0.6149 - auc: 0.9246 - prc: 0.7280 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8500 - val_recall: 0.7391 - val_auc: 0.9127 - val_prc: 0.7748\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 42/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.1589e-04 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2045.0000 - 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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0048 - tp: 36.0000 - fp: 5.0000 - tn: 30649.0000 - fn: 30.0000 - accuracy: 0.9989 - precision: 0.8780 - recall: 0.5455 - auc: 0.9159 - prc: 0.7505         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 71.0000 - fp: 11.0000 - tn: 59257.0000 - fn: 53.0000 - accuracy: 0.9989 - precision: 0.8659 - recall: 0.5726 - auc: 0.9184 - prc: 0.7377"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 106.0000 - fp: 12.0000 - tn: 87881.0000 - fn: 65.0000 - accuracy: 0.9991 - precision: 0.8983 - recall: 0.6199 - auc: 0.9320 - prc: 0.7875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0036 - tp: 128.0000 - fp: 17.0000 - tn: 114464.0000 - fn: 79.0000 - accuracy: 0.9992 - precision: 0.8828 - recall: 0.6184 - auc: 0.9316 - prc: 0.7779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0036 - tp: 162.0000 - fp: 22.0000 - tn: 143083.0000 - fn: 93.0000 - accuracy: 0.9992 - precision: 0.8804 - recall: 0.6353 - auc: 0.9326 - prc: 0.7666"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - ETA: 0s - loss: 0.0037 - tp: 190.0000 - fp: 28.0000 - tn: 171703.0000 - fn: 111.0000 - accuracy: 0.9992 - precision: 0.8716 - recall: 0.6312 - auc: 0.9328 - prc: 0.7544"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 201.0000 - fp: 31.0000 - tn: 181923.0000 - fn: 121.0000 - accuracy: 0.9992 - precision: 0.8664 - recall: 0.6242 - auc: 0.9325 - prc: 0.7437 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 9.0000 - val_tn: 45491.0000 - val_fn: 18.0000 - val_accuracy: 0.9994 - val_precision: 0.8500 - val_recall: 0.7391 - val_auc: 0.9127 - val_prc: 0.7726\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 43/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0029 - tp: 1.0000 - fp: 1.0000 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9985 - precision: 0.5000 - recall: 0.3333 - auc: 0.9993 - 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\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0039 - tp: 27.0000 - fp: 9.0000 - tn: 30657.0000 - fn: 27.0000 - accuracy: 0.9988 - precision: 0.7500 - recall: 0.5000 - auc: 0.9712 - prc: 0.7232"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 59.0000 - fp: 14.0000 - tn: 59262.0000 - fn: 57.0000 - accuracy: 0.9988 - precision: 0.8082 - recall: 0.5086 - auc: 0.9517 - prc: 0.7287"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 91.0000 - fp: 20.0000 - tn: 87878.0000 - fn: 75.0000 - accuracy: 0.9989 - precision: 0.8198 - recall: 0.5482 - auc: 0.9420 - prc: 0.7269"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0043 - tp: 114.0000 - fp: 27.0000 - tn: 116499.0000 - fn: 96.0000 - accuracy: 0.9989 - precision: 0.8085 - recall: 0.5429 - auc: 0.9325 - prc: 0.7110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0040 - tp: 144.0000 - fp: 31.0000 - tn: 145120.0000 - fn: 113.0000 - accuracy: 0.9990 - precision: 0.8229 - recall: 0.5603 - auc: 0.9311 - prc: 0.7205"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 177.0000 - fp: 35.0000 - tn: 173730.0000 - fn: 138.0000 - accuracy: 0.9990 - precision: 0.8349 - recall: 0.5619 - auc: 0.9261 - prc: 0.7158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0042 - tp: 182.0000 - fp: 36.0000 - tn: 181918.0000 - fn: 140.0000 - accuracy: 0.9990 - precision: 0.8349 - recall: 0.5652 - auc: 0.9261 - prc: 0.7135 - val_loss: 0.0031 - 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: 0.9127 - val_prc: 0.7750\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 44/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 4.9326e-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: 0.0032 - tp: 26.0000 - fp: 5.0000 - tn: 28627.0000 - fn: 14.0000 - accuracy: 0.9993 - precision: 0.8387 - recall: 0.6500 - auc: 0.9495 - prc: 0.7360         "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 59.0000 - fp: 6.0000 - tn: 57238.0000 - fn: 41.0000 - accuracy: 0.9992 - precision: 0.9077 - recall: 0.5900 - auc: 0.9293 - 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",
      "42/90 [=============>................] - ETA: 0s - loss: 0.0037 - tp: 85.0000 - fp: 9.0000 - tn: 85864.0000 - fn: 58.0000 - accuracy: 0.9992 - precision: 0.9043 - recall: 0.5944 - auc: 0.9258 - prc: 0.7488"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 118.0000 - fp: 14.0000 - tn: 114477.0000 - fn: 79.0000 - accuracy: 0.9992 - precision: 0.8939 - recall: 0.5990 - auc: 0.9256 - prc: 0.7329"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0036 - tp: 152.0000 - fp: 21.0000 - tn: 143094.0000 - fn: 93.0000 - accuracy: 0.9992 - precision: 0.8786 - recall: 0.6204 - auc: 0.9381 - prc: 0.7565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - ETA: 0s - loss: 0.0036 - tp: 183.0000 - fp: 24.0000 - tn: 171713.0000 - fn: 112.0000 - accuracy: 0.9992 - precision: 0.8841 - recall: 0.6203 - auc: 0.9383 - prc: 0.7577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 199.0000 - fp: 24.0000 - tn: 181930.0000 - fn: 123.0000 - accuracy: 0.9992 - precision: 0.8924 - recall: 0.6180 - auc: 0.9325 - prc: 0.7531 - val_loss: 0.0031 - 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: 0.9127 - val_prc: 0.7713\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 45/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0016 - 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",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0032 - tp: 30.0000 - fp: 1.0000 - tn: 30671.0000 - fn: 18.0000 - accuracy: 0.9994 - precision: 0.9677 - recall: 0.6250 - auc: 0.9367 - prc: 0.7748 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0034 - tp: 62.0000 - fp: 9.0000 - tn: 59288.0000 - fn: 33.0000 - accuracy: 0.9993 - precision: 0.8732 - recall: 0.6526 - auc: 0.9361 - prc: 0.7572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0033 - tp: 90.0000 - fp: 12.0000 - tn: 87911.0000 - fn: 51.0000 - accuracy: 0.9993 - precision: 0.8824 - recall: 0.6383 - auc: 0.9354 - prc: 0.7558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0035 - tp: 132.0000 - fp: 14.0000 - tn: 116517.0000 - fn: 73.0000 - accuracy: 0.9993 - precision: 0.9041 - recall: 0.6439 - auc: 0.9383 - prc: 0.7674"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0038 - tp: 155.0000 - fp: 22.0000 - tn: 145131.0000 - fn: 100.0000 - accuracy: 0.9992 - precision: 0.8757 - recall: 0.6078 - auc: 0.9345 - prc: 0.7464"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 188.0000 - fp: 27.0000 - tn: 173747.0000 - fn: 118.0000 - accuracy: 0.9992 - precision: 0.8744 - recall: 0.6144 - auc: 0.9322 - 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\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - tp: 200.0000 - fp: 29.0000 - tn: 181925.0000 - fn: 122.0000 - accuracy: 0.9992 - precision: 0.8734 - recall: 0.6211 - auc: 0.9340 - prc: 0.7505 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.9107 - val_recall: 0.7391 - val_auc: 0.9126 - val_prc: 0.7779\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 46/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0038 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.5000 - auc: 0.9987 - prc: 0.8216"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 34.0000 - fp: 3.0000 - tn: 28615.0000 - fn: 20.0000 - accuracy: 0.9992 - precision: 0.9189 - recall: 0.6296 - auc: 0.9343 - prc: 0.7703 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 62.0000 - fp: 5.0000 - tn: 55182.0000 - fn: 47.0000 - accuracy: 0.9991 - precision: 0.9254 - recall: 0.5688 - auc: 0.9394 - prc: 0.7469"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 89.0000 - fp: 10.0000 - tn: 81758.0000 - fn: 63.0000 - accuracy: 0.9991 - precision: 0.8990 - recall: 0.5855 - auc: 0.9398 - prc: 0.7277"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 120.0000 - fp: 16.0000 - tn: 108330.0000 - fn: 78.0000 - accuracy: 0.9991 - precision: 0.8824 - recall: 0.6061 - auc: 0.9461 - prc: 0.7359"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0038 - tp: 146.0000 - fp: 19.0000 - tn: 136958.0000 - fn: 93.0000 - accuracy: 0.9992 - precision: 0.8848 - recall: 0.6109 - auc: 0.9489 - prc: 0.7411"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 178.0000 - fp: 24.0000 - tn: 163525.0000 - fn: 113.0000 - accuracy: 0.9992 - precision: 0.8812 - recall: 0.6117 - auc: 0.9423 - prc: 0.7312"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 195.0000 - fp: 25.0000 - tn: 181929.0000 - fn: 127.0000 - accuracy: 0.9992 - precision: 0.8864 - recall: 0.6056 - auc: 0.9416 - prc: 0.7341 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.9107 - val_recall: 0.7391 - val_auc: 0.9126 - val_prc: 0.7761\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 47/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0120 - 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: 0.7456 - prc: 0.2756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.0000 - tn: 28616.0000 - fn: 25.0000 - accuracy: 0.9991 - precision: 0.9355 - recall: 0.5370 - auc: 0.8972 - prc: 0.7232             "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0046 - tp: 58.0000 - fp: 10.0000 - tn: 57229.0000 - fn: 47.0000 - accuracy: 0.9990 - precision: 0.8529 - recall: 0.5524 - auc: 0.8988 - prc: 0.6857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 85.0000 - fp: 14.0000 - tn: 85850.0000 - fn: 67.0000 - accuracy: 0.9991 - precision: 0.8586 - recall: 0.5592 - auc: 0.9167 - prc: 0.7256"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 116.0000 - fp: 20.0000 - tn: 112418.0000 - fn: 86.0000 - accuracy: 0.9991 - precision: 0.8529 - recall: 0.5743 - auc: 0.9173 - 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\b\b\b\r",
      "69/90 [======================>.......] - ETA: 0s - loss: 0.0040 - tp: 140.0000 - fp: 30.0000 - tn: 141041.0000 - fn: 101.0000 - accuracy: 0.9991 - precision: 0.8235 - recall: 0.5809 - auc: 0.9202 - prc: 0.7167"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 183.0000 - fp: 39.0000 - tn: 169641.0000 - fn: 121.0000 - accuracy: 0.9991 - precision: 0.8243 - recall: 0.6020 - auc: 0.9283 - prc: 0.7261"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 192.0000 - fp: 40.0000 - tn: 181914.0000 - fn: 130.0000 - accuracy: 0.9991 - precision: 0.8276 - recall: 0.5963 - auc: 0.9307 - prc: 0.7235 - val_loss: 0.0031 - val_tp: 48.0000 - val_fp: 4.0000 - val_tn: 45496.0000 - val_fn: 21.0000 - val_accuracy: 0.9995 - val_precision: 0.9231 - val_recall: 0.6957 - val_auc: 0.9127 - val_prc: 0.7792\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 48/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0050 - tp: 3.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 1.0000 - accuracy: 0.9995 - precision: 1.0000 - recall: 0.7500 - auc: 0.8741 - 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\r",
      "15/90 [====>.........................] - ETA: 0s - loss: 0.0038 - tp: 37.0000 - fp: 4.0000 - tn: 30658.0000 - fn: 21.0000 - accuracy: 0.9992 - precision: 0.9024 - recall: 0.6379 - auc: 0.9390 - prc: 0.7616 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 70.0000 - fp: 10.0000 - tn: 59273.0000 - fn: 39.0000 - accuracy: 0.9992 - precision: 0.8750 - recall: 0.6422 - auc: 0.9349 - prc: 0.7297"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0040 - tp: 97.0000 - fp: 13.0000 - tn: 87892.0000 - fn: 62.0000 - accuracy: 0.9991 - precision: 0.8818 - recall: 0.6101 - auc: 0.9268 - 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\r",
      "57/90 [==================>...........] - ETA: 0s - loss: 0.0038 - tp: 134.0000 - fp: 20.0000 - tn: 116502.0000 - fn: 80.0000 - accuracy: 0.9991 - precision: 0.8701 - recall: 0.6262 - auc: 0.9338 - prc: 0.7477"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "71/90 [======================>.......] - ETA: 0s - loss: 0.0038 - tp: 166.0000 - fp: 26.0000 - tn: 145118.0000 - fn: 98.0000 - accuracy: 0.9991 - precision: 0.8646 - recall: 0.6288 - auc: 0.9329 - prc: 0.7521"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0036 - tp: 196.0000 - fp: 28.0000 - tn: 173743.0000 - fn: 113.0000 - accuracy: 0.9992 - precision: 0.8750 - recall: 0.6343 - auc: 0.9377 - 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\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - tp: 205.0000 - fp: 30.0000 - tn: 181924.0000 - fn: 117.0000 - accuracy: 0.9992 - precision: 0.8723 - recall: 0.6366 - auc: 0.9371 - prc: 0.7668 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 5.0000 - val_tn: 45495.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.9107 - val_recall: 0.7391 - val_auc: 0.9127 - val_prc: 0.7772\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 49/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0029 - tp: 2.0000 - fp: 0.0000e+00 - tn: 2044.0000 - fn: 2.0000 - accuracy: 0.9990 - precision: 1.0000 - recall: 0.5000 - auc: 0.9993 - prc: 0.8431"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0041 - tp: 26.0000 - fp: 8.0000 - tn: 28617.0000 - fn: 21.0000 - accuracy: 0.9990 - precision: 0.7647 - recall: 0.5532 - auc: 0.9139 - 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\r",
      "27/90 [========>.....................] - ETA: 0s - loss: 0.0048 - tp: 55.0000 - fp: 12.0000 - tn: 55183.0000 - fn: 46.0000 - accuracy: 0.9990 - precision: 0.8209 - recall: 0.5446 - auc: 0.8999 - prc: 0.6691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 90.0000 - fp: 15.0000 - tn: 81755.0000 - fn: 60.0000 - accuracy: 0.9991 - precision: 0.8571 - recall: 0.6000 - auc: 0.9258 - prc: 0.7424"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 114.0000 - fp: 23.0000 - tn: 108329.0000 - fn: 78.0000 - accuracy: 0.9991 - precision: 0.8321 - recall: 0.5938 - auc: 0.9340 - prc: 0.7214"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 140.0000 - fp: 27.0000 - tn: 134907.0000 - fn: 94.0000 - accuracy: 0.9991 - precision: 0.8383 - recall: 0.5983 - auc: 0.9351 - prc: 0.7316"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0039 - tp: 170.0000 - fp: 29.0000 - tn: 161480.0000 - fn: 113.0000 - accuracy: 0.9991 - precision: 0.8543 - recall: 0.6007 - auc: 0.9303 - prc: 0.7314"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 39.\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 [==============================] - 0s 5ms/step - loss: 0.0038 - tp: 198.0000 - fp: 32.0000 - tn: 181922.0000 - fn: 124.0000 - accuracy: 0.9991 - precision: 0.8609 - recall: 0.6149 - auc: 0.9308 - prc: 0.7420 - val_loss: 0.0031 - val_tp: 51.0000 - val_fp: 7.0000 - val_tn: 45493.0000 - val_fn: 18.0000 - val_accuracy: 0.9995 - val_precision: 0.8793 - val_recall: 0.7391 - val_auc: 0.9127 - val_prc: 0.7790\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 49: 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": [
    "### トレーニング履歴を確認する\n",
    "\n",
    "このセクションでは、トレーニングと検証のセットでモデルの精度と損失のプロットを作成します。これらは、過適合をチェックするのに役立ちます。詳細については、[過適合と学習不足](https://www.tensorflow.org/tutorials/keras/overfit_and_underfit)チュートリアルを参照してください。\n",
    "\n",
    "さらに、上で作成した任意のメトリクスのプロットを作成することができます。 例として、下記には偽陰性が含まれています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:42.190592Z",
     "iopub.status.busy": "2022-12-14T23:06:42.189995Z",
     "iopub.status.idle": "2022-12-14T23:06:42.196100Z",
     "shell.execute_reply": "2022-12-14T23:06:42.195381Z"
    },
    "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": "2022-12-14T23:06:42.199334Z",
     "iopub.status.busy": "2022-12-14T23:06:42.198749Z",
     "iopub.status.idle": "2022-12-14T23:06:42.684668Z",
     "shell.execute_reply": "2022-12-14T23:06:42.684033Z"
    },
    "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": [
    "注意: 一般的に、検証曲線はトレーニング曲線よりも優れています。 これは主に、モデルを評価する際にドロップアウトレイヤーがアクティブでないということに起因します。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aJC1booryouo"
   },
   "source": [
    "### メトリクスを評価する\n",
    "\n",
    "[混同行列](https://developers.google.com/machine-learning/glossary/#confusion_matrix)を使用して、実際のラベルと予測されたラベルを要約できます。ここで、X 軸は予測されたラベルであり、Y 軸は実際のラベルです。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:42.688996Z",
     "iopub.status.busy": "2022-12-14T23:06:42.688762Z",
     "iopub.status.idle": "2022-12-14T23:06:43.097057Z",
     "shell.execute_reply": "2022-12-14T23:06:43.096366Z"
    },
    "id": "aNS796IJKrev"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 4s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "84/90 [===========================>..] - 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: 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",
      "28/28 [==============================] - 0s 1ms/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": "2022-12-14T23:06:43.100565Z",
     "iopub.status.busy": "2022-12-14T23:06:43.099927Z",
     "iopub.status.idle": "2022-12-14T23:06:43.104827Z",
     "shell.execute_reply": "2022-12-14T23:06:43.104254Z"
    },
    "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": [
    "テストデータセットでモデルを評価し、上記で作成した行列の結果を表示します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.108072Z",
     "iopub.status.busy": "2022-12-14T23:06:43.107515Z",
     "iopub.status.idle": "2022-12-14T23:06:43.419527Z",
     "shell.execute_reply": "2022-12-14T23:06:43.418902Z"
    },
    "id": "poh_hZngt2_9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.002801472321152687\n",
      "tp :  71.0\n",
      "fp :  1.0\n",
      "tn :  56860.0\n",
      "fn :  30.0\n",
      "accuracy :  0.9994557499885559\n",
      "precision :  0.9861111044883728\n",
      "recall :  0.7029703259468079\n",
      "auc :  0.9403578639030457\n",
      "prc :  0.8531444072723389\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Legitimate Transactions Detected (True Negatives):  56860\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  1\n",
      "Fraudulent Transactions Missed (False Negatives):  30\n",
      "Fraudulent Transactions Detected (True Positives):  71\n",
      "Total Fraudulent Transactions:  101\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "モデルがすべてを完璧に予測した場合は、これは[対角行列](https://en.wikipedia.org/wiki/Diagonal_matrix)になり、主な対角線から外れた値が不正確な予測を示してゼロになります。 この場合、行列は偽陽性が比較的少ないことを示し、これは誤ってフラグが立てられた正当な取引が比較的少ないことを意味します。 しかし、偽陽性の数が増えればコストがかかる可能性はありますが、偽陰性の数はさらに少なくした方が良いでしょう。偽陽性は顧客にカード利用履歴の確認を求めるメールを送信する可能性があるのに対し、偽陰性は不正な取引を成立させてしまう可能性があるため、このトレードオフはむしろ望ましいといえます。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "P-QpQsip_F2Q"
   },
   "source": [
    "### ROC をプロットする\n",
    "\n",
    "次に、[ROC](https://developers.google.com/machine-learning/glossary#ROC) をプロットします。このプロットは、出力しきい値を調整するだけでモデルが到達できるパフォーマンス範囲が一目で分かるので有用です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.423106Z",
     "iopub.status.busy": "2022-12-14T23:06:43.422626Z",
     "iopub.status.idle": "2022-12-14T23:06:43.427186Z",
     "shell.execute_reply": "2022-12-14T23:06:43.426553Z"
    },
    "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": "2022-12-14T23:06:43.430106Z",
     "iopub.status.busy": "2022-12-14T23:06:43.429651Z",
     "iopub.status.idle": "2022-12-14T23:06:43.656033Z",
     "shell.execute_reply": "2022-12-14T23:06:43.655361Z"
    },
    "id": "DfHHspttKJE0"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### AUPRC をプロットする\n",
    "\n",
    "[AUPRC](https://developers.google.com/machine-learning/glossary?hl=en#PR_AUC) をプロットします。補間された適合率-再現率曲線の下の領域は、分類しきい値のさまざまな値に対して（再現率、適合率）点をプロットすることにより取得できます。計算方法によっては、PR AUC はモデルの平均適合率と同等になる場合があります。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.659777Z",
     "iopub.status.busy": "2022-12-14T23:06:43.659278Z",
     "iopub.status.idle": "2022-12-14T23:06:43.663324Z",
     "shell.execute_reply": "2022-12-14T23:06:43.662780Z"
    },
    "id": "XV6JSlFGEqGI"
   },
   "outputs": [],
   "source": [
    "def plot_prc(name, labels, predictions, **kwargs):\r\n",
    "    precision, recall, _ = sklearn.metrics.precision_recall_curve(labels, predictions)\r\n",
    "\r\n",
    "    plt.plot(precision, recall, label=name, linewidth=2, **kwargs)\r\n",
    "    plt.xlabel('Precision')\r\n",
    "    plt.ylabel('Recall')\r\n",
    "    plt.grid(True)\r\n",
    "    ax = plt.gca()\r\n",
    "    ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.666492Z",
     "iopub.status.busy": "2022-12-14T23:06:43.665963Z",
     "iopub.status.idle": "2022-12-14T23:06:43.883761Z",
     "shell.execute_reply": "2022-12-14T23:06:43.883026Z"
    },
    "id": "FdQs_PcqEsiL"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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])\r\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\r\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gpdsFyp64DhY"
   },
   "source": [
    "適合率は比較的高いように見えますが、再現率と ROC 曲線の下の曲線下面積 (AUC) は、期待するほど高いものではありません。適合率と再現率の両方を最大化しようとすると、分類器はしばしば課題に直面します。不均衡データセットを扱う場合は特にそうです。大切な問題のコンテキストでは異なるタイプのエラーにかかるコストを考慮することが重要です。 この例では、偽陰性（不正な取引が見逃されている）は金銭的コストを伴う可能性がある一方で、偽陽性（取引が不正であると誤ってフラグが立てられている）はユーザーの幸福度を低下させる可能性があります。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cveQoiMyGQCo"
   },
   "source": [
    "## クラスの重み"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ePGp6GUE1WfH"
   },
   "source": [
    "### クラスの重みを計算する\n",
    "\n",
    "最終目的は不正な取引を特定することですが、処理する陽性サンプルがそれほど多くないので、利用可能な数少ない例の分類器に大きな重み付けをします。 これを行うには、パラメータを介して各クラスの重みを Keras に渡します。 これにより、モデルは十分に表現されていないクラスの例にも「より注意を払う」ようになります。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.887918Z",
     "iopub.status.busy": "2022-12-14T23:06:43.887539Z",
     "iopub.status.idle": "2022-12-14T23:06:43.892216Z",
     "shell.execute_reply": "2022-12-14T23:06:43.891559Z"
    },
    "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": [
    "### クラスの重みでモデルをトレーニングする\n",
    "\n",
    "次に、クラスの重みでモデルを再トレーニングして評価し、それが予測にどのように影響するかを確認します。\n",
    "\n",
    "注意: `class_weights` を使用すると、損失の範囲が変更されます。オプティマイザにもよりますが、これはトレーニングの安定性に影響を与える可能性があります。`tf.keras.optimizers.SGD` のように、ステップサイズが勾配の大きさに依存するオプティマイザは失敗する可能性があります。ここで使用されているオプティマイザ `tf.keras.optimizers.Adam` は、スケーリングの変更による影響を受けません。また、重み付けのため、総損失は 2 つのモデル間で比較できないことに注意してください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:43.895420Z",
     "iopub.status.busy": "2022-12-14T23:06:43.894917Z",
     "iopub.status.idle": "2022-12-14T23:06:52.809513Z",
     "shell.execute_reply": "2022-12-14T23:06:52.808819Z"
    },
    "id": "UJ589fn8ST3x"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 2:03 - loss: 6.3158 - tp: 71.0000 - fp: 2.0000 - tn: 58901.0000 - fn: 36.0000 - accuracy: 0.9994 - precision: 0.9726 - recall: 0.6636 - auc: 0.9201 - prc: 0.8042"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3.4539 - tp: 72.0000 - fp: 18.0000 - tn: 83421.0000 - fn: 75.0000 - accuracy: 0.9989 - precision: 0.8000 - recall: 0.4898 - auc: 0.8465 - prc: 0.5520 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3.0005 - tp: 75.0000 - fp: 28.0000 - tn: 107945.0000 - fn: 114.0000 - accuracy: 0.9987 - precision: 0.7282 - recall: 0.3968 - auc: 0.8241 - prc: 0.4508"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.9126 - tp: 80.0000 - fp: 49.0000 - tn: 134500.0000 - fn: 157.0000 - accuracy: 0.9985 - precision: 0.6202 - recall: 0.3376 - auc: 0.8007 - prc: 0.3612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.8114 - tp: 86.0000 - fp: 74.0000 - tn: 161050.0000 - fn: 200.0000 - accuracy: 0.9983 - precision: 0.5375 - recall: 0.3007 - auc: 0.7930 - prc: 0.3143"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.6399 - tp: 103.0000 - fp: 104.0000 - tn: 185545.0000 - fn: 234.0000 - accuracy: 0.9982 - precision: 0.4976 - recall: 0.3056 - auc: 0.8022 - prc: 0.3064"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.5352 - tp: 123.0000 - fp: 123.0000 - tn: 210051.0000 - fn: 265.0000 - accuracy: 0.9982 - precision: 0.5000 - recall: 0.3170 - auc: 0.8049 - prc: 0.3139"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2.3207 - tp: 132.0000 - fp: 160.0000 - tn: 234562.0000 - fn: 284.0000 - accuracy: 0.9981 - precision: 0.4521 - recall: 0.3173 - auc: 0.8066 - prc: 0.2845"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 [==============================] - 2s 11ms/step - loss: 2.3129 - tp: 133.0000 - fp: 165.0000 - tn: 238650.0000 - fn: 290.0000 - accuracy: 0.9981 - precision: 0.4463 - recall: 0.3144 - auc: 0.8058 - prc: 0.2802 - val_loss: 0.0063 - val_tp: 27.0000 - val_fp: 8.0000 - val_tn: 45492.0000 - val_fn: 42.0000 - val_accuracy: 0.9989 - val_precision: 0.7714 - val_recall: 0.3913 - val_auc: 0.8841 - val_prc: 0.5301\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0400 - tp: 3.0000 - fp: 3.0000 - tn: 2042.0000 - fn: 0.0000e+00 - accuracy: 0.9985 - precision: 0.5000 - 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",
      "13/90 [===>..........................] - ETA: 0s - loss: 1.2245 - tp: 27.0000 - fp: 53.0000 - tn: 26521.0000 - fn: 23.0000 - accuracy: 0.9971 - precision: 0.3375 - recall: 0.5400 - auc: 0.8646 - prc: 0.4199"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.4537 - tp: 49.0000 - fp: 108.0000 - tn: 53039.0000 - fn: 52.0000 - accuracy: 0.9970 - precision: 0.3121 - recall: 0.4851 - auc: 0.8515 - prc: 0.3542"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.3070 - tp: 71.0000 - fp: 148.0000 - tn: 77538.0000 - fn: 67.0000 - accuracy: 0.9972 - precision: 0.3242 - recall: 0.5145 - auc: 0.8604 - prc: 0.3898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.2124 - tp: 100.0000 - fp: 198.0000 - tn: 102017.0000 - fn: 85.0000 - accuracy: 0.9972 - precision: 0.3356 - recall: 0.5405 - auc: 0.8706 - prc: 0.4134"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.2201 - tp: 125.0000 - fp: 236.0000 - tn: 128553.0000 - fn: 110.0000 - accuracy: 0.9973 - precision: 0.3463 - recall: 0.5319 - auc: 0.8764 - prc: 0.4112"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.1544 - tp: 147.0000 - fp: 298.0000 - tn: 155076.0000 - fn: 127.0000 - accuracy: 0.9973 - precision: 0.3303 - recall: 0.5365 - auc: 0.8785 - prc: 0.4073"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.0917 - tp: 180.0000 - fp: 370.0000 - tn: 181580.0000 - fn: 142.0000 - accuracy: 0.9972 - precision: 0.3273 - recall: 0.5590 - auc: 0.8846 - prc: 0.4262"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.0916 - tp: 180.0000 - fp: 370.0000 - tn: 181584.0000 - fn: 142.0000 - accuracy: 0.9972 - precision: 0.3273 - recall: 0.5590 - auc: 0.8846 - prc: 0.4262 - val_loss: 0.0072 - val_tp: 49.0000 - val_fp: 18.0000 - val_tn: 45482.0000 - val_fn: 20.0000 - val_accuracy: 0.9992 - val_precision: 0.7313 - val_recall: 0.7101 - val_auc: 0.8941 - val_prc: 0.5897\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0062 - tp: 0.0000e+00 - fp: 3.0000 - tn: 2045.0000 - fn: 0.0000e+00 - accuracy: 0.9985 - 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",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.7028 - tp: 43.0000 - fp: 78.0000 - tn: 28536.0000 - fn: 15.0000 - accuracy: 0.9968 - precision: 0.3554 - recall: 0.7414 - auc: 0.9436 - prc: 0.5510                    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.9812 - tp: 68.0000 - fp: 148.0000 - tn: 55041.0000 - fn: 39.0000 - accuracy: 0.9966 - precision: 0.3148 - recall: 0.6355 - auc: 0.9143 - prc: 0.4669"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.8320 - tp: 95.0000 - fp: 215.0000 - tn: 79514.0000 - fn: 48.0000 - accuracy: 0.9967 - precision: 0.3065 - recall: 0.6643 - auc: 0.9243 - prc: 0.5155"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7897 - tp: 118.0000 - fp: 295.0000 - tn: 106019.0000 - fn: 64.0000 - accuracy: 0.9966 - precision: 0.2857 - recall: 0.6484 - auc: 0.9200 - prc: 0.4820"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.8131 - tp: 147.0000 - fp: 384.0000 - tn: 132508.0000 - fn: 81.0000 - accuracy: 0.9965 - precision: 0.2768 - recall: 0.6447 - auc: 0.9153 - prc: 0.4650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7819 - tp: 189.0000 - fp: 460.0000 - tn: 159002.0000 - fn: 93.0000 - accuracy: 0.9965 - precision: 0.2912 - recall: 0.6702 - auc: 0.9198 - prc: 0.4971"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7963 - tp: 216.0000 - fp: 544.0000 - tn: 181410.0000 - fn: 106.0000 - accuracy: 0.9964 - precision: 0.2842 - recall: 0.6708 - auc: 0.9169 - prc: 0.4917 - val_loss: 0.0090 - val_tp: 53.0000 - val_fp: 22.0000 - val_tn: 45478.0000 - val_fn: 16.0000 - val_accuracy: 0.9992 - val_precision: 0.7067 - val_recall: 0.7681 - val_auc: 0.9043 - val_prc: 0.6168\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0133 - tp: 4.0000 - fp: 16.0000 - tn: 2028.0000 - fn: 0.0000e+00 - accuracy: 0.9922 - precision: 0.2000 - recall: 1.0000 - auc: 0.9998 - prc: 0.8000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6905 - tp: 42.0000 - fp: 117.0000 - tn: 28497.0000 - fn: 16.0000 - accuracy: 0.9954 - precision: 0.2642 - recall: 0.7241 - auc: 0.9369 - prc: 0.5762"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7463 - tp: 77.0000 - fp: 200.0000 - tn: 52941.0000 - fn: 30.0000 - accuracy: 0.9957 - precision: 0.2780 - recall: 0.7196 - auc: 0.9320 - prc: 0.5558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6948 - tp: 101.0000 - fp: 303.0000 - tn: 77380.0000 - fn: 40.0000 - accuracy: 0.9956 - precision: 0.2500 - recall: 0.7163 - auc: 0.9306 - prc: 0.5137"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6957 - tp: 131.0000 - fp: 430.0000 - tn: 103832.0000 - fn: 55.0000 - accuracy: 0.9954 - precision: 0.2335 - recall: 0.7043 - auc: 0.9254 - prc: 0.4801"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6579 - tp: 172.0000 - fp: 542.0000 - tn: 128245.0000 - fn: 65.0000 - accuracy: 0.9953 - precision: 0.2409 - recall: 0.7257 - auc: 0.9316 - prc: 0.5149"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6177 - tp: 207.0000 - fp: 662.0000 - tn: 152659.0000 - fn: 72.0000 - accuracy: 0.9952 - precision: 0.2382 - recall: 0.7419 - auc: 0.9325 - prc: 0.5429"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6061 - tp: 239.0000 - fp: 794.0000 - tn: 179110.0000 - fn: 81.0000 - accuracy: 0.9951 - precision: 0.2314 - recall: 0.7469 - auc: 0.9296 - 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\r",
      "90/90 [==============================] - 0s 5ms/step - loss: 0.6105 - tp: 240.0000 - fp: 800.0000 - tn: 181154.0000 - fn: 82.0000 - accuracy: 0.9952 - precision: 0.2308 - recall: 0.7453 - auc: 0.9281 - prc: 0.5541 - val_loss: 0.0114 - val_tp: 53.0000 - val_fp: 34.0000 - val_tn: 45466.0000 - val_fn: 16.0000 - val_accuracy: 0.9989 - val_precision: 0.6092 - val_recall: 0.7681 - val_auc: 0.9200 - val_prc: 0.6427\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0212 - tp: 7.0000 - fp: 13.0000 - tn: 2028.0000 - fn: 0.0000e+00 - accuracy: 0.9937 - precision: 0.3500 - recall: 1.0000 - auc: 0.9993 - prc: 0.7000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5156 - tp: 48.0000 - fp: 148.0000 - tn: 28466.0000 - fn: 10.0000 - accuracy: 0.9945 - precision: 0.2449 - recall: 0.8276 - auc: 0.9468 - prc: 0.6402"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5944 - tp: 85.0000 - fp: 309.0000 - tn: 54878.0000 - fn: 24.0000 - accuracy: 0.9940 - precision: 0.2157 - recall: 0.7798 - auc: 0.9416 - prc: 0.5428"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6068 - tp: 123.0000 - fp: 460.0000 - tn: 81298.0000 - fn: 39.0000 - accuracy: 0.9939 - precision: 0.2110 - recall: 0.7593 - auc: 0.9408 - prc: 0.5355"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5815 - tp: 147.0000 - fp: 610.0000 - tn: 107735.0000 - fn: 52.0000 - accuracy: 0.9939 - precision: 0.1942 - recall: 0.7387 - auc: 0.9399 - prc: 0.5080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5367 - tp: 179.0000 - fp: 803.0000 - tn: 134126.0000 - fn: 60.0000 - accuracy: 0.9936 - precision: 0.1823 - recall: 0.7490 - auc: 0.9443 - prc: 0.5043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5314 - tp: 212.0000 - fp: 998.0000 - tn: 160512.0000 - fn: 70.0000 - accuracy: 0.9934 - precision: 0.1752 - recall: 0.7518 - auc: 0.9405 - prc: 0.4952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5837 - tp: 240.0000 - fp: 1179.0000 - tn: 180775.0000 - fn: 82.0000 - accuracy: 0.9931 - precision: 0.1691 - recall: 0.7453 - auc: 0.9288 - prc: 0.4826 - val_loss: 0.0152 - val_tp: 54.0000 - val_fp: 72.0000 - val_tn: 45428.0000 - val_fn: 15.0000 - val_accuracy: 0.9981 - val_precision: 0.4286 - val_recall: 0.7826 - val_auc: 0.9307 - val_prc: 0.6217\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.9643 - tp: 5.0000 - fp: 9.0000 - tn: 2033.0000 - fn: 1.0000 - accuracy: 0.9951 - precision: 0.3571 - recall: 0.8333 - auc: 0.8890 - prc: 0.7555"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3627 - tp: 38.0000 - fp: 212.0000 - tn: 28413.0000 - fn: 9.0000 - accuracy: 0.9923 - precision: 0.1520 - recall: 0.8085 - auc: 0.9397 - prc: 0.4764"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5200 - tp: 75.0000 - fp: 445.0000 - tn: 54754.0000 - fn: 22.0000 - accuracy: 0.9916 - precision: 0.1442 - recall: 0.7732 - auc: 0.9303 - prc: 0.4181"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4667 - tp: 116.0000 - fp: 657.0000 - tn: 81117.0000 - fn: 30.0000 - accuracy: 0.9916 - precision: 0.1501 - recall: 0.7945 - auc: 0.9415 - prc: 0.4610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4782 - tp: 164.0000 - fp: 886.0000 - tn: 107455.0000 - fn: 39.0000 - accuracy: 0.9915 - precision: 0.1562 - recall: 0.8079 - auc: 0.9397 - prc: 0.4867"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4828 - tp: 196.0000 - fp: 1127.0000 - tn: 133795.0000 - fn: 50.0000 - accuracy: 0.9913 - precision: 0.1481 - recall: 0.7967 - auc: 0.9347 - prc: 0.4645"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4566 - tp: 229.0000 - fp: 1391.0000 - tn: 160115.0000 - fn: 57.0000 - accuracy: 0.9911 - precision: 0.1414 - recall: 0.8007 - auc: 0.9378 - prc: 0.4611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4503 - tp: 259.0000 - fp: 1631.0000 - tn: 180323.0000 - fn: 63.0000 - accuracy: 0.9907 - precision: 0.1370 - recall: 0.8043 - auc: 0.9382 - prc: 0.4635 - val_loss: 0.0195 - val_tp: 54.0000 - val_fp: 121.0000 - val_tn: 45379.0000 - val_fn: 15.0000 - val_accuracy: 0.9970 - val_precision: 0.3086 - val_recall: 0.7826 - val_auc: 0.9420 - val_prc: 0.6180\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0199 - tp: 3.0000 - fp: 23.0000 - tn: 2022.0000 - fn: 0.0000e+00 - accuracy: 0.9888 - precision: 0.1154 - recall: 1.0000 - auc: 0.9995 - prc: 0.6000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1764 - tp: 34.0000 - fp: 299.0000 - tn: 28335.0000 - fn: 4.0000 - accuracy: 0.9894 - precision: 0.1021 - recall: 0.8947 - auc: 0.9763 - prc: 0.5245 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2585 - tp: 73.0000 - fp: 559.0000 - tn: 54651.0000 - fn: 13.0000 - accuracy: 0.9897 - precision: 0.1155 - recall: 0.8488 - auc: 0.9682 - prc: 0.5303"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2186 - tp: 119.0000 - fp: 862.0000 - tn: 80922.0000 - fn: 17.0000 - accuracy: 0.9893 - precision: 0.1213 - recall: 0.8750 - auc: 0.9775 - prc: 0.5188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2733 - tp: 155.0000 - fp: 1175.0000 - tn: 107189.0000 - fn: 25.0000 - accuracy: 0.9889 - precision: 0.1165 - recall: 0.8611 - auc: 0.9678 - prc: 0.4957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3298 - tp: 194.0000 - fp: 1509.0000 - tn: 133428.0000 - fn: 37.0000 - accuracy: 0.9886 - precision: 0.1139 - recall: 0.8398 - auc: 0.9626 - prc: 0.4843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3610 - tp: 233.0000 - fp: 1832.0000 - tn: 159677.0000 - fn: 50.0000 - accuracy: 0.9884 - precision: 0.1128 - recall: 0.8233 - auc: 0.9609 - prc: 0.4684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3774 - tp: 265.0000 - fp: 2116.0000 - tn: 179838.0000 - fn: 57.0000 - accuracy: 0.9881 - precision: 0.1113 - recall: 0.8230 - auc: 0.9587 - prc: 0.4556 - val_loss: 0.0247 - val_tp: 54.0000 - val_fp: 180.0000 - val_tn: 45320.0000 - val_fn: 15.0000 - val_accuracy: 0.9957 - val_precision: 0.2308 - val_recall: 0.7826 - val_auc: 0.9448 - val_prc: 0.6166\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0150 - tp: 0.0000e+00 - fp: 12.0000 - tn: 2036.0000 - fn: 0.0000e+00 - accuracy: 0.9941 - 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\b\r",
      "14/90 [===>..........................] - ETA: 0s - loss: 0.4706 - tp: 35.0000 - fp: 359.0000 - tn: 28266.0000 - fn: 12.0000 - accuracy: 0.9871 - precision: 0.0888 - recall: 0.7447 - auc: 0.9118 - prc: 0.3694                    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4227 - tp: 63.0000 - fp: 733.0000 - tn: 54481.0000 - fn: 19.0000 - accuracy: 0.9864 - precision: 0.0791 - recall: 0.7683 - auc: 0.9226 - prc: 0.3716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4233 - tp: 92.0000 - fp: 1078.0000 - tn: 78675.0000 - fn: 27.0000 - accuracy: 0.9862 - precision: 0.0786 - recall: 0.7731 - auc: 0.9235 - prc: 0.3823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4388 - tp: 139.0000 - fp: 1468.0000 - tn: 104851.0000 - fn: 38.0000 - accuracy: 0.9859 - precision: 0.0865 - recall: 0.7853 - auc: 0.9314 - prc: 0.3944"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4183 - tp: 186.0000 - fp: 1840.0000 - tn: 131050.0000 - fn: 44.0000 - accuracy: 0.9858 - precision: 0.0918 - recall: 0.8087 - auc: 0.9371 - prc: 0.4145"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4055 - tp: 228.0000 - fp: 2293.0000 - tn: 157173.0000 - fn: 50.0000 - accuracy: 0.9853 - precision: 0.0904 - recall: 0.8201 - auc: 0.9379 - prc: 0.3905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3911 - tp: 267.0000 - fp: 2627.0000 - tn: 179327.0000 - fn: 55.0000 - accuracy: 0.9853 - precision: 0.0923 - recall: 0.8292 - auc: 0.9403 - prc: 0.3966 - val_loss: 0.0300 - val_tp: 56.0000 - val_fp: 271.0000 - val_tn: 45229.0000 - val_fn: 13.0000 - val_accuracy: 0.9938 - val_precision: 0.1713 - val_recall: 0.8116 - val_auc: 0.9574 - val_prc: 0.5708\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0287 - tp: 2.0000 - fp: 34.0000 - tn: 2012.0000 - fn: 0.0000e+00 - accuracy: 0.9834 - precision: 0.0556 - recall: 1.0000 - auc: 0.9998 - prc: 0.6667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4114 - tp: 33.0000 - fp: 468.0000 - tn: 28160.0000 - fn: 11.0000 - accuracy: 0.9833 - precision: 0.0659 - recall: 0.7500 - auc: 0.9487 - prc: 0.2544"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3475 - tp: 73.0000 - fp: 900.0000 - tn: 54306.0000 - fn: 17.0000 - accuracy: 0.9834 - precision: 0.0750 - recall: 0.8111 - auc: 0.9575 - prc: 0.2911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3594 - tp: 115.0000 - fp: 1352.0000 - tn: 80429.0000 - fn: 24.0000 - accuracy: 0.9832 - precision: 0.0784 - recall: 0.8273 - auc: 0.9558 - prc: 0.3053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2935 - tp: 154.0000 - fp: 1824.0000 - tn: 106540.0000 - fn: 26.0000 - accuracy: 0.9830 - precision: 0.0779 - recall: 0.8556 - auc: 0.9646 - prc: 0.3155"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3411 - tp: 189.0000 - fp: 2259.0000 - tn: 132682.0000 - fn: 38.0000 - accuracy: 0.9830 - precision: 0.0772 - recall: 0.8326 - auc: 0.9534 - prc: 0.3107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3292 - tp: 226.0000 - fp: 2752.0000 - tn: 158771.0000 - fn: 43.0000 - accuracy: 0.9827 - precision: 0.0759 - recall: 0.8401 - auc: 0.9531 - prc: 0.3178"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3524 - tp: 269.0000 - fp: 3140.0000 - tn: 178814.0000 - fn: 53.0000 - accuracy: 0.9825 - precision: 0.0789 - recall: 0.8354 - auc: 0.9525 - prc: 0.3345 - val_loss: 0.0372 - val_tp: 56.0000 - val_fp: 399.0000 - val_tn: 45101.0000 - val_fn: 13.0000 - val_accuracy: 0.9910 - val_precision: 0.1231 - val_recall: 0.8116 - val_auc: 0.9583 - val_prc: 0.5338\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0348 - tp: 2.0000 - fp: 51.0000 - tn: 1995.0000 - fn: 0.0000e+00 - accuracy: 0.9751 - precision: 0.0377 - recall: 1.0000 - auc: 0.9993 - prc: 0.4361"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3063 - tp: 34.0000 - fp: 504.0000 - tn: 26081.0000 - fn: 5.0000 - accuracy: 0.9809 - precision: 0.0632 - recall: 0.8718 - auc: 0.9356 - prc: 0.3177 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3398 - tp: 69.0000 - fp: 1033.0000 - tn: 52131.0000 - fn: 15.0000 - accuracy: 0.9803 - precision: 0.0626 - recall: 0.8214 - auc: 0.9451 - 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\b\r",
      "39/90 [============>.................] - ETA: 0s - loss: 0.2942 - tp: 111.0000 - fp: 1561.0000 - tn: 78182.0000 - fn: 18.0000 - accuracy: 0.9802 - precision: 0.0664 - recall: 0.8605 - auc: 0.9530 - prc: 0.3139"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3963 - tp: 149.0000 - fp: 2114.0000 - tn: 104200.0000 - fn: 33.0000 - accuracy: 0.9798 - precision: 0.0658 - recall: 0.8187 - auc: 0.9352 - prc: 0.2934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4263 - tp: 194.0000 - fp: 2584.0000 - tn: 128250.0000 - fn: 44.0000 - accuracy: 0.9799 - precision: 0.0698 - recall: 0.8151 - auc: 0.9327 - prc: 0.3005"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3737 - tp: 234.0000 - fp: 3153.0000 - tn: 154262.0000 - fn: 47.0000 - accuracy: 0.9797 - precision: 0.0691 - recall: 0.8327 - auc: 0.9418 - prc: 0.3001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 270.0000 - fp: 3654.0000 - tn: 178300.0000 - fn: 52.0000 - accuracy: 0.9797 - precision: 0.0688 - recall: 0.8385 - auc: 0.9472 - prc: 0.2990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3474 - tp: 270.0000 - fp: 3654.0000 - tn: 178300.0000 - fn: 52.0000 - accuracy: 0.9797 - precision: 0.0688 - recall: 0.8385 - auc: 0.9472 - prc: 0.2990 - val_loss: 0.0435 - val_tp: 56.0000 - val_fp: 492.0000 - val_tn: 45008.0000 - val_fn: 13.0000 - val_accuracy: 0.9889 - val_precision: 0.1022 - val_recall: 0.8116 - val_auc: 0.9581 - val_prc: 0.5103\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0380 - tp: 6.0000 - fp: 44.0000 - tn: 1998.0000 - fn: 0.0000e+00 - accuracy: 0.9785 - precision: 0.1200 - recall: 1.0000 - auc: 0.9990 - prc: 0.6000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2865 - tp: 49.0000 - fp: 655.0000 - tn: 27962.0000 - fn: 6.0000 - accuracy: 0.9769 - precision: 0.0696 - recall: 0.8909 - auc: 0.9563 - prc: 0.3649 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3148 - tp: 100.0000 - fp: 1244.0000 - tn: 53939.0000 - fn: 13.0000 - accuracy: 0.9773 - precision: 0.0744 - recall: 0.8850 - auc: 0.9570 - prc: 0.3697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2989 - tp: 132.0000 - fp: 1851.0000 - tn: 79918.0000 - fn: 19.0000 - accuracy: 0.9772 - precision: 0.0666 - recall: 0.8742 - auc: 0.9557 - prc: 0.3356"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3209 - tp: 162.0000 - fp: 2414.0000 - tn: 105943.0000 - fn: 25.0000 - accuracy: 0.9775 - precision: 0.0629 - recall: 0.8663 - auc: 0.9461 - prc: 0.3159"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3439 - tp: 199.0000 - fp: 3000.0000 - tn: 131937.0000 - fn: 32.0000 - accuracy: 0.9776 - precision: 0.0622 - recall: 0.8615 - auc: 0.9388 - prc: 0.3098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3725 - tp: 244.0000 - fp: 3588.0000 - tn: 157918.0000 - fn: 42.0000 - accuracy: 0.9776 - precision: 0.0637 - recall: 0.8531 - auc: 0.9369 - prc: 0.3039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3760 - tp: 274.0000 - fp: 4014.0000 - tn: 177940.0000 - fn: 48.0000 - accuracy: 0.9777 - precision: 0.0639 - recall: 0.8509 - auc: 0.9363 - prc: 0.2969 - val_loss: 0.0488 - val_tp: 57.0000 - val_fp: 552.0000 - val_tn: 44948.0000 - val_fn: 12.0000 - val_accuracy: 0.9876 - val_precision: 0.0936 - val_recall: 0.8261 - val_auc: 0.9582 - val_prc: 0.4941\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0427 - tp: 2.0000 - fp: 46.0000 - tn: 2000.0000 - fn: 0.0000e+00 - accuracy: 0.9775 - precision: 0.0417 - recall: 1.0000 - auc: 0.9993 - prc: 0.4000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2063 - tp: 38.0000 - fp: 643.0000 - tn: 25938.0000 - fn: 5.0000 - accuracy: 0.9757 - precision: 0.0558 - recall: 0.8837 - auc: 0.9824 - prc: 0.2842 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2299 - tp: 83.0000 - fp: 1247.0000 - tn: 49860.0000 - fn: 10.0000 - accuracy: 0.9754 - precision: 0.0624 - recall: 0.8925 - auc: 0.9758 - prc: 0.3276"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2846 - tp: 120.0000 - fp: 1860.0000 - tn: 75825.0000 - fn: 19.0000 - accuracy: 0.9759 - precision: 0.0606 - recall: 0.8633 - auc: 0.9669 - prc: 0.3078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3217 - tp: 162.0000 - fp: 2520.0000 - tn: 101739.0000 - fn: 27.0000 - accuracy: 0.9756 - precision: 0.0604 - recall: 0.8571 - auc: 0.9571 - prc: 0.3013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3080 - tp: 204.0000 - fp: 3217.0000 - tn: 127618.0000 - fn: 33.0000 - accuracy: 0.9752 - precision: 0.0596 - recall: 0.8608 - auc: 0.9582 - prc: 0.2958"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3088 - tp: 237.0000 - fp: 3844.0000 - tn: 151528.0000 - fn: 39.0000 - accuracy: 0.9751 - precision: 0.0581 - recall: 0.8587 - auc: 0.9559 - prc: 0.2846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3119 - tp: 269.0000 - fp: 4494.0000 - tn: 175415.0000 - fn: 46.0000 - accuracy: 0.9748 - precision: 0.0565 - recall: 0.8540 - auc: 0.9557 - prc: 0.2764"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3090 - tp: 276.0000 - fp: 4542.0000 - tn: 177412.0000 - fn: 46.0000 - accuracy: 0.9748 - precision: 0.0573 - recall: 0.8571 - auc: 0.9566 - prc: 0.2807 - val_loss: 0.0552 - val_tp: 58.0000 - val_fp: 625.0000 - val_tn: 44875.0000 - val_fn: 11.0000 - val_accuracy: 0.9860 - val_precision: 0.0849 - val_recall: 0.8406 - val_auc: 0.9611 - val_prc: 0.4743\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0518 - tp: 5.0000 - fp: 67.0000 - tn: 1976.0000 - fn: 0.0000e+00 - accuracy: 0.9673 - precision: 0.0694 - recall: 1.0000 - auc: 0.9985 - prc: 0.4545"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2324 - tp: 33.0000 - fp: 669.0000 - tn: 25917.0000 - fn: 5.0000 - accuracy: 0.9747 - precision: 0.0470 - recall: 0.8684 - auc: 0.9648 - prc: 0.2084 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2857 - tp: 62.0000 - fp: 1313.0000 - tn: 49815.0000 - fn: 10.0000 - accuracy: 0.9742 - precision: 0.0451 - recall: 0.8611 - auc: 0.9396 - prc: 0.2026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2916 - tp: 100.0000 - fp: 1949.0000 - tn: 73709.0000 - fn: 18.0000 - accuracy: 0.9740 - precision: 0.0488 - recall: 0.8475 - auc: 0.9502 - prc: 0.2228"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2543 - tp: 146.0000 - fp: 2639.0000 - tn: 99594.0000 - fn: 21.0000 - accuracy: 0.9740 - precision: 0.0524 - recall: 0.8743 - auc: 0.9603 - prc: 0.2439"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2759 - tp: 186.0000 - fp: 3359.0000 - tn: 125450.0000 - fn: 29.0000 - accuracy: 0.9737 - precision: 0.0525 - recall: 0.8651 - auc: 0.9568 - prc: 0.2346"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2916 - tp: 224.0000 - fp: 4002.0000 - tn: 149337.0000 - fn: 37.0000 - accuracy: 0.9737 - precision: 0.0530 - recall: 0.8582 - auc: 0.9560 - prc: 0.2355"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2916 - tp: 269.0000 - fp: 4692.0000 - tn: 173172.0000 - fn: 43.0000 - accuracy: 0.9734 - precision: 0.0542 - recall: 0.8622 - auc: 0.9565 - prc: 0.2432"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3053 - tp: 277.0000 - fp: 4807.0000 - tn: 177147.0000 - fn: 45.0000 - accuracy: 0.9734 - precision: 0.0545 - recall: 0.8602 - auc: 0.9528 - prc: 0.2449 - val_loss: 0.0600 - val_tp: 58.0000 - val_fp: 670.0000 - val_tn: 44830.0000 - val_fn: 11.0000 - val_accuracy: 0.9851 - val_precision: 0.0797 - val_recall: 0.8406 - val_auc: 0.9603 - val_prc: 0.4704\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 0s - loss: 0.0563 - tp: 5.0000 - fp: 60.0000 - tn: 1983.0000 - fn: 0.0000e+00 - accuracy: 0.9707 - precision: 0.0769 - recall: 1.0000 - auc: 0.9987 - prc: 0.4905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3693 - tp: 48.0000 - fp: 710.0000 - tn: 27905.0000 - fn: 9.0000 - accuracy: 0.9749 - precision: 0.0633 - recall: 0.8421 - auc: 0.9550 - prc: 0.2861 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3933 - tp: 98.0000 - fp: 1473.0000 - tn: 53709.0000 - fn: 16.0000 - accuracy: 0.9731 - precision: 0.0624 - recall: 0.8596 - auc: 0.9469 - prc: 0.2659"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3463 - tp: 136.0000 - fp: 2226.0000 - tn: 79537.0000 - fn: 21.0000 - accuracy: 0.9726 - precision: 0.0576 - recall: 0.8662 - auc: 0.9490 - prc: 0.2594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3075 - tp: 180.0000 - fp: 2985.0000 - tn: 105355.0000 - fn: 24.0000 - accuracy: 0.9723 - precision: 0.0569 - recall: 0.8824 - auc: 0.9558 - prc: 0.2589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3165 - tp: 220.0000 - fp: 3747.0000 - tn: 131171.0000 - fn: 30.0000 - accuracy: 0.9721 - precision: 0.0555 - recall: 0.8800 - auc: 0.9506 - prc: 0.2558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3186 - tp: 260.0000 - fp: 4499.0000 - tn: 156996.0000 - fn: 37.0000 - accuracy: 0.9720 - precision: 0.0546 - recall: 0.8754 - auc: 0.9518 - prc: 0.2507"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 4.\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 [==============================] - 0s 5ms/step - loss: 0.3006 - tp: 283.0000 - fp: 5045.0000 - tn: 176909.0000 - fn: 39.0000 - accuracy: 0.9721 - precision: 0.0531 - recall: 0.8789 - auc: 0.9527 - prc: 0.2479 - val_loss: 0.0620 - val_tp: 58.0000 - val_fp: 689.0000 - val_tn: 44811.0000 - val_fn: 11.0000 - val_accuracy: 0.9846 - val_precision: 0.0776 - val_recall: 0.8406 - val_auc: 0.9613 - val_prc: 0.4712\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14: 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": [
    "### トレーニング履歴を確認する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:52.813246Z",
     "iopub.status.busy": "2022-12-14T23:06:52.812620Z",
     "iopub.status.idle": "2022-12-14T23:06:53.312052Z",
     "shell.execute_reply": "2022-12-14T23:06:53.311408Z"
    },
    "id": "BBe9FMO5ucTC"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### メトリクスを評価する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:53.315812Z",
     "iopub.status.busy": "2022-12-14T23:06:53.315551Z",
     "iopub.status.idle": "2022-12-14T23:06:53.695047Z",
     "shell.execute_reply": "2022-12-14T23:06:53.694357Z"
    },
    "id": "nifqscPGw-5w"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/90 [..............................] - ETA: 4s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 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",
      "28/28 [==============================] - 0s 1ms/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": "2022-12-14T23:06:53.698832Z",
     "iopub.status.busy": "2022-12-14T23:06:53.698274Z",
     "iopub.status.idle": "2022-12-14T23:06:54.226149Z",
     "shell.execute_reply": "2022-12-14T23:06:54.225515Z"
    },
    "id": "owKL2vdMBJr6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.00944011565297842\n",
      "tp :  81.0\n",
      "fp :  29.0\n",
      "tn :  56832.0\n",
      "fn :  20.0\n",
      "accuracy :  0.9991397857666016\n",
      "precision :  0.7363636493682861\n",
      "recall :  0.801980197429657\n",
      "auc :  0.9742780327796936\n",
      "prc :  0.7228649854660034\n",
      "\n",
      "Legitimate Transactions Detected (True Negatives):  56832\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  29\n",
      "Fraudulent Transactions Missed (False Negatives):  20\n",
      "Fraudulent Transactions Detected (True Positives):  81\n",
      "Total Fraudulent Transactions:  101\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "ここでは、クラスの重みを使用すると偽陽性が多くなるため、正解率と適合率が低くなりますが、逆にモデルがより多くの真陽性を検出したため、再現率と AUC が高くなっていることが分かります。このモデルは正解率は低いものの、再現率が高くなるので、より多くの不正取引を特定します。もちろん、両タイプのエラーにはコストがかかります。（あまりにも多くの正当な取引を不正取引としてフラグを立ててユーザーに迷惑をかけたくはないはずです。）アプリケーションのこういった異なるタイプのエラー間のトレードオフは、慎重に検討してください"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hXDAwyr0HYdX"
   },
   "source": [
    "### ROC をプロットする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:54.229949Z",
     "iopub.status.busy": "2022-12-14T23:06:54.229342Z",
     "iopub.status.idle": "2022-12-14T23:06:54.514680Z",
     "shell.execute_reply": "2022-12-14T23:06:54.514041Z"
    },
    "id": "3hzScIVZS1Xm"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### AUPRC をプロットする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:54.518378Z",
     "iopub.status.busy": "2022-12-14T23:06:54.518085Z",
     "iopub.status.idle": "2022-12-14T23:06:54.815886Z",
     "shell.execute_reply": "2022-12-14T23:06:54.815212Z"
    },
    "id": "7jHnmVebOWOC"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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])\r\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\r\n",
    "\r\n",
    "plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\r\n",
    "plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\r\n",
    "\r\n",
    "\r\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5ysRtr6xHnXP"
   },
   "source": [
    "## オーバーサンプリング"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "18VUHNc-UF5w"
   },
   "source": [
    "### マイノリティクラスをオーバーサンプリングする\n",
    "\n",
    "関連したアプローチとして、マイノリティクラスをオーバーサンプリングしてデータセットを再サンプルするという方法があります。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:54.820387Z",
     "iopub.status.busy": "2022-12-14T23:06:54.819798Z",
     "iopub.status.idle": "2022-12-14T23:06:54.842633Z",
     "shell.execute_reply": "2022-12-14T23:06:54.841891Z"
    },
    "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": [
    "#### NumPy を使用する\n",
    "\n",
    "陽性の例から適切な数のランダムインデックスを選択して、手動でデータセットのバランスをとることができます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:54.846750Z",
     "iopub.status.busy": "2022-12-14T23:06:54.846286Z",
     "iopub.status.idle": "2022-12-14T23:06:54.868905Z",
     "shell.execute_reply": "2022-12-14T23:06:54.868180Z"
    },
    "id": "BUzGjSkwqT88"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(181954, 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": "2022-12-14T23:06:54.872265Z",
     "iopub.status.busy": "2022-12-14T23:06:54.871686Z",
     "iopub.status.idle": "2022-12-14T23:06:54.975340Z",
     "shell.execute_reply": "2022-12-14T23:06:54.974693Z"
    },
    "id": "7ie_FFet6cep"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(363908, 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": [
    "#### `tf.data`を使用する"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "usyixaST8v5P"
   },
   "source": [
    "もし`tf.data`を使用している場合、バランスの取れた例を作成する最も簡単な方法は、`positive`と`negative`のデータセットから開始し、それらをマージすることです。その他の例については、[tf.data ガイド](../../guide/data.ipynb)をご覧ください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:54.979495Z",
     "iopub.status.busy": "2022-12-14T23:06:54.978888Z",
     "iopub.status.idle": "2022-12-14T23:06:55.074478Z",
     "shell.execute_reply": "2022-12-14T23:06:55.073846Z"
    },
    "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": [
    "各データセットは`(feature, label)`のペアを提供します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:55.078361Z",
     "iopub.status.busy": "2022-12-14T23:06:55.077748Z",
     "iopub.status.idle": "2022-12-14T23:06:55.094613Z",
     "shell.execute_reply": "2022-12-14T23:06:55.094024Z"
    },
    "id": "llXc9rNH7Fbz"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Features:\n",
      " [-2.19541086  1.13428993 -1.53623679 -0.33658631 -0.83969674 -1.57367972\n",
      " -1.68012623  0.22759802  0.26401501 -3.5197414   2.45072394 -3.59505942\n",
      " -1.02811684 -5.          1.80441222 -3.70754897 -5.         -2.22095608\n",
      " -0.01134361 -0.93004871  0.75601008 -0.0947461  -1.75493901  0.44294128\n",
      " -0.03893845 -2.00270316 -2.29191024  0.00709538  0.57125601]\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": [
    "`tf.data.Dataset.sample_from_datasets` を使用し、この 2 つをマージします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:55.098199Z",
     "iopub.status.busy": "2022-12-14T23:06:55.097590Z",
     "iopub.status.idle": "2022-12-14T23:06:55.119924Z",
     "shell.execute_reply": "2022-12-14T23:06:55.119285Z"
    },
    "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": "2022-12-14T23:06:55.123291Z",
     "iopub.status.busy": "2022-12-14T23:06:55.122697Z",
     "iopub.status.idle": "2022-12-14T23:06:55.372335Z",
     "shell.execute_reply": "2022-12-14T23:06:55.371512Z"
    },
    "id": "EWXARdTdAuQK"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.47705078125\n"
     ]
    }
   ],
   "source": [
    "for features, label in resampled_ds.take(1):\n",
    "  print(label.numpy().mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "irgqf3YxAyN0"
   },
   "source": [
    "このデータセットを使用するには、エポックごとのステップ数が必要です。\n",
    "\n",
    "この場合の「エポック」の定義はあまり明確ではありません。それぞれの陰性の例を 1 度見るのに必要なバッチ数だとしましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:55.375701Z",
     "iopub.status.busy": "2022-12-14T23:06:55.375406Z",
     "iopub.status.idle": "2022-12-14T23:06:55.380407Z",
     "shell.execute_reply": "2022-12-14T23:06:55.379682Z"
    },
    "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": [
    "### オーバーサンプリングデータをトレーニングする\n",
    "\n",
    "ここで、クラスの重みを使用する代わりに、再サンプルされたデータセットを使用してモデルをトレーニングし、それらの手法がどう比較されるかを確認してみましょう。\n",
    "\n",
    "注意: 陽性の例を複製することでデータのバランスをとっているため、データセットの総サイズは大きくなり、各エポックではより多くのトレーニングステップが実行されます。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:55.383582Z",
     "iopub.status.busy": "2022-12-14T23:06:55.383106Z",
     "iopub.status.idle": "2022-12-14T23:08:02.964792Z",
     "shell.execute_reply": "2022-12-14T23:08:02.963977Z"
    },
    "id": "soRQ89JYqd6b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 7:04 - loss: 1.3562 - tp: 424.0000 - fp: 241.0000 - tn: 57664.0000 - fn: 681.0000 - accuracy: 0.9844 - precision: 0.6376 - recall: 0.3837 - auc: 0.9152 - prc: 0.5123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.3267 - tp: 2340.0000 - fp: 1465.0000 - tn: 61518.0000 - fn: 3927.0000 - accuracy: 0.9221 - precision: 0.6150 - recall: 0.3734 - auc: 0.8806 - prc: 0.5655"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.2621 - tp: 3673.0000 - fp: 2273.0000 - tn: 63769.0000 - fn: 5679.0000 - accuracy: 0.8945 - precision: 0.6177 - recall: 0.3928 - auc: 0.8717 - prc: 0.5934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 1.1991 - tp: 5133.0000 - fp: 3052.0000 - tn: 66078.0000 - fn: 7275.0000 - accuracy: 0.8733 - precision: 0.6271 - recall: 0.4137 - auc: 0.8648 - prc: 0.6180"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 1.1482 - tp: 6792.0000 - fp: 3867.0000 - tn: 68268.0000 - fn: 8755.0000 - accuracy: 0.8560 - precision: 0.6372 - recall: 0.4369 - auc: 0.8595 - prc: 0.6417"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 1.1031 - tp: 8472.0000 - fp: 4689.0000 - tn: 70543.0000 - fn: 10122.0000 - accuracy: 0.8421 - precision: 0.6437 - recall: 0.4556 - auc: 0.8537 - prc: 0.6583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 1.0614 - tp: 10315.0000 - fp: 5505.0000 - tn: 72782.0000 - fn: 11368.0000 - accuracy: 0.8312 - precision: 0.6520 - recall: 0.4757 - auc: 0.8497 - prc: 0.6757"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 1.0258 - tp: 12151.0000 - fp: 6364.0000 - tn: 75032.0000 - fn: 12567.0000 - accuracy: 0.8216 - precision: 0.6563 - recall: 0.4916 - auc: 0.8458 - prc: 0.6886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.9908 - tp: 14108.0000 - fp: 7213.0000 - tn: 77283.0000 - fn: 13654.0000 - accuracy: 0.8141 - precision: 0.6617 - recall: 0.5082 - auc: 0.8431 - prc: 0.7018"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.9596 - tp: 16154.0000 - fp: 8065.0000 - tn: 79487.0000 - fn: 14696.0000 - accuracy: 0.8078 - precision: 0.6670 - recall: 0.5236 - auc: 0.8412 - prc: 0.7146"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.9281 - tp: 18302.0000 - fp: 8863.0000 - tn: 81744.0000 - fn: 15637.0000 - accuracy: 0.8033 - precision: 0.6737 - recall: 0.5393 - auc: 0.8405 - prc: 0.7277"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.9026 - tp: 20492.0000 - fp: 9765.0000 - tn: 83905.0000 - fn: 16528.0000 - accuracy: 0.7988 - precision: 0.6773 - recall: 0.5535 - auc: 0.8395 - prc: 0.7380"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.8775 - tp: 22681.0000 - fp: 10669.0000 - tn: 86153.0000 - fn: 17331.0000 - accuracy: 0.7954 - precision: 0.6801 - recall: 0.5669 - auc: 0.8388 - prc: 0.7471"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.8558 - tp: 24934.0000 - fp: 11557.0000 - tn: 88325.0000 - fn: 18162.0000 - accuracy: 0.7921 - precision: 0.6833 - recall: 0.5786 - auc: 0.8384 - prc: 0.7556"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.8360 - tp: 27278.0000 - fp: 12410.0000 - tn: 90496.0000 - fn: 18938.0000 - accuracy: 0.7898 - precision: 0.6873 - recall: 0.5902 - auc: 0.8384 - prc: 0.7638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.8169 - tp: 29593.0000 - fp: 13254.0000 - tn: 92729.0000 - fn: 19690.0000 - accuracy: 0.7878 - precision: 0.6907 - recall: 0.6005 - auc: 0.8385 - prc: 0.7715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7994 - tp: 31904.0000 - fp: 14094.0000 - tn: 95021.0000 - fn: 20391.0000 - accuracy: 0.7864 - precision: 0.6936 - recall: 0.6101 - auc: 0.8386 - prc: 0.7781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7837 - tp: 34289.0000 - fp: 14896.0000 - tn: 97259.0000 - fn: 21110.0000 - accuracy: 0.7851 - precision: 0.6971 - recall: 0.6189 - auc: 0.8390 - prc: 0.7844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7688 - tp: 36681.0000 - fp: 15732.0000 - tn: 99512.0000 - fn: 21773.0000 - accuracy: 0.7841 - precision: 0.6998 - recall: 0.6275 - auc: 0.8394 - prc: 0.7903"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7542 - tp: 39108.0000 - fp: 16530.0000 - tn: 101822.0000 - fn: 22382.0000 - accuracy: 0.7836 - precision: 0.7029 - recall: 0.6360 - auc: 0.8402 - prc: 0.7961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7405 - tp: 41581.0000 - fp: 17274.0000 - tn: 104135.0000 - fn: 22996.0000 - accuracy: 0.7835 - precision: 0.7065 - recall: 0.6439 - auc: 0.8411 - prc: 0.8017"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7282 - tp: 44031.0000 - fp: 17986.0000 - tn: 106506.0000 - fn: 23607.0000 - accuracy: 0.7835 - precision: 0.7100 - recall: 0.6510 - auc: 0.8418 - prc: 0.8066"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7158 - tp: 46535.0000 - fp: 18682.0000 - tn: 108842.0000 - fn: 24215.0000 - accuracy: 0.7836 - precision: 0.7135 - recall: 0.6577 - auc: 0.8428 - prc: 0.8116"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7045 - tp: 48962.0000 - fp: 19390.0000 - tn: 111248.0000 - fn: 24818.0000 - accuracy: 0.7837 - precision: 0.7163 - recall: 0.6636 - auc: 0.8437 - prc: 0.8159"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6939 - tp: 51413.0000 - fp: 20057.0000 - tn: 113681.0000 - fn: 25411.0000 - accuracy: 0.7841 - precision: 0.7194 - recall: 0.6692 - auc: 0.8446 - 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\r",
      " 78/278 [=======>......................] - ETA: 3s - loss: 0.6841 - tp: 53868.0000 - fp: 20705.0000 - tn: 116092.0000 - fn: 26041.0000 - accuracy: 0.7843 - precision: 0.7224 - recall: 0.6741 - auc: 0.8455 - prc: 0.8238"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6746 - tp: 56379.0000 - fp: 21348.0000 - tn: 118505.0000 - fn: 26618.0000 - accuracy: 0.7848 - precision: 0.7253 - recall: 0.6793 - auc: 0.8465 - prc: 0.8275"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6656 - tp: 58934.0000 - fp: 21963.0000 - tn: 120878.0000 - fn: 27219.0000 - accuracy: 0.7852 - precision: 0.7285 - recall: 0.6841 - auc: 0.8475 - prc: 0.8312"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6568 - tp: 61438.0000 - fp: 22601.0000 - tn: 123324.0000 - fn: 27775.0000 - accuracy: 0.7858 - precision: 0.7311 - recall: 0.6887 - auc: 0.8485 - prc: 0.8346"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6482 - tp: 64030.0000 - fp: 23198.0000 - tn: 125777.0000 - fn: 28277.0000 - accuracy: 0.7867 - precision: 0.7341 - recall: 0.6937 - auc: 0.8498 - prc: 0.8381"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6405 - tp: 66541.0000 - fp: 23835.0000 - tn: 128221.0000 - fn: 28829.0000 - accuracy: 0.7872 - precision: 0.7363 - recall: 0.6977 - auc: 0.8508 - prc: 0.8410"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6329 - tp: 69052.0000 - fp: 24425.0000 - tn: 130732.0000 - fn: 29361.0000 - accuracy: 0.7879 - precision: 0.7387 - recall: 0.7017 - auc: 0.8518 - prc: 0.8438"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.6256 - tp: 71642.0000 - fp: 24983.0000 - tn: 133207.0000 - fn: 29882.0000 - accuracy: 0.7887 - precision: 0.7414 - recall: 0.7057 - auc: 0.8529 - prc: 0.8467"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6183 - tp: 74192.0000 - fp: 25515.0000 - tn: 135762.0000 - fn: 30389.0000 - accuracy: 0.7897 - precision: 0.7441 - recall: 0.7094 - auc: 0.8541 - prc: 0.8495"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6117 - tp: 76778.0000 - fp: 26053.0000 - tn: 138264.0000 - fn: 30907.0000 - accuracy: 0.7906 - precision: 0.7466 - recall: 0.7130 - auc: 0.8552 - prc: 0.8521"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6050 - tp: 79421.0000 - fp: 26537.0000 - tn: 140760.0000 - fn: 31428.0000 - accuracy: 0.7916 - precision: 0.7496 - recall: 0.7165 - auc: 0.8564 - 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\r",
      "111/278 [==========>...................] - ETA: 3s - loss: 0.5989 - tp: 81966.0000 - fp: 27087.0000 - tn: 143298.0000 - fn: 31939.0000 - accuracy: 0.7924 - precision: 0.7516 - recall: 0.7196 - auc: 0.8574 - prc: 0.8570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5927 - tp: 84644.0000 - fp: 27552.0000 - tn: 145800.0000 - fn: 32438.0000 - accuracy: 0.7934 - precision: 0.7544 - recall: 0.7229 - auc: 0.8586 - prc: 0.8595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5869 - tp: 87183.0000 - fp: 28070.0000 - tn: 148400.0000 - fn: 32925.0000 - accuracy: 0.7943 - precision: 0.7564 - recall: 0.7259 - auc: 0.8596 - prc: 0.8616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5813 - tp: 89776.0000 - fp: 28534.0000 - tn: 150998.0000 - fn: 33414.0000 - accuracy: 0.7954 - precision: 0.7588 - recall: 0.7288 - auc: 0.8607 - prc: 0.8638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5758 - tp: 92413.0000 - fp: 28999.0000 - tn: 153554.0000 - fn: 33900.0000 - accuracy: 0.7964 - precision: 0.7612 - recall: 0.7316 - auc: 0.8618 - prc: 0.8659"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5701 - tp: 95068.0000 - fp: 29436.0000 - tn: 156126.0000 - fn: 34380.0000 - accuracy: 0.7974 - precision: 0.7636 - recall: 0.7344 - auc: 0.8630 - prc: 0.8681"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5646 - tp: 97664.0000 - fp: 29852.0000 - tn: 158810.0000 - fn: 34828.0000 - accuracy: 0.7986 - precision: 0.7659 - recall: 0.7371 - auc: 0.8641 - prc: 0.8701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.5597 - tp: 100267.0000 - fp: 30308.0000 - tn: 161416.0000 - fn: 35307.0000 - accuracy: 0.7995 - precision: 0.7679 - recall: 0.7396 - auc: 0.8651 - prc: 0.8718"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.5547 - tp: 102936.0000 - fp: 30737.0000 - tn: 164017.0000 - fn: 35752.0000 - accuracy: 0.8006 - precision: 0.7701 - recall: 0.7422 - auc: 0.8663 - prc: 0.8737"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.5500 - tp: 105517.0000 - fp: 31156.0000 - tn: 166710.0000 - fn: 36203.0000 - accuracy: 0.8016 - precision: 0.7720 - recall: 0.7445 - auc: 0.8673 - prc: 0.8754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.5455 - tp: 108150.0000 - fp: 31592.0000 - tn: 169321.0000 - fn: 36667.0000 - accuracy: 0.8026 - precision: 0.7739 - recall: 0.7468 - auc: 0.8683 - prc: 0.8770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5409 - tp: 110787.0000 - fp: 31997.0000 - tn: 171980.0000 - fn: 37110.0000 - accuracy: 0.8036 - precision: 0.7759 - recall: 0.7491 - auc: 0.8693 - prc: 0.8787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.5366 - tp: 113407.0000 - fp: 32385.0000 - tn: 174668.0000 - fn: 37558.0000 - accuracy: 0.8046 - precision: 0.7779 - recall: 0.7512 - auc: 0.8703 - prc: 0.8803"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5324 - tp: 116026.0000 - fp: 32770.0000 - tn: 177338.0000 - fn: 38028.0000 - accuracy: 0.8056 - precision: 0.7798 - recall: 0.7532 - auc: 0.8713 - prc: 0.8817"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "153/278 [===============>..............] - ETA: 2s - loss: 0.5282 - tp: 118652.0000 - fp: 33154.0000 - tn: 180028.0000 - fn: 38472.0000 - accuracy: 0.8066 - precision: 0.7816 - recall: 0.7551 - auc: 0.8723 - prc: 0.8832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5241 - tp: 121307.0000 - fp: 33517.0000 - tn: 182697.0000 - fn: 38929.0000 - accuracy: 0.8076 - precision: 0.7835 - recall: 0.7571 - auc: 0.8733 - prc: 0.8847"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5202 - tp: 123988.0000 - fp: 33889.0000 - tn: 185330.0000 - fn: 39387.0000 - accuracy: 0.8085 - precision: 0.7853 - recall: 0.7589 - auc: 0.8743 - prc: 0.8861"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5165 - tp: 126617.0000 - fp: 34248.0000 - tn: 188018.0000 - fn: 39855.0000 - accuracy: 0.8094 - precision: 0.7871 - recall: 0.7606 - auc: 0.8752 - prc: 0.8875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5127 - tp: 129274.0000 - fp: 34585.0000 - tn: 190732.0000 - fn: 40291.0000 - accuracy: 0.8104 - precision: 0.7889 - recall: 0.7624 - auc: 0.8761 - prc: 0.8888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5089 - tp: 132071.0000 - fp: 34890.0000 - tn: 193349.0000 - fn: 40716.0000 - accuracy: 0.8115 - precision: 0.7910 - recall: 0.7644 - auc: 0.8771 - prc: 0.8903"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5052 - tp: 134684.0000 - fp: 35221.0000 - tn: 196133.0000 - fn: 41132.0000 - accuracy: 0.8125 - precision: 0.7927 - recall: 0.7661 - auc: 0.8781 - prc: 0.8915"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5018 - tp: 137328.0000 - fp: 35544.0000 - tn: 198871.0000 - fn: 41571.0000 - accuracy: 0.8134 - precision: 0.7944 - recall: 0.7676 - auc: 0.8790 - prc: 0.8927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4983 - tp: 139929.0000 - fp: 35849.0000 - tn: 201677.0000 - fn: 42003.0000 - accuracy: 0.8144 - precision: 0.7961 - recall: 0.7691 - auc: 0.8799 - prc: 0.8939"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.4949 - tp: 142595.0000 - fp: 36170.0000 - tn: 204419.0000 - fn: 42418.0000 - accuracy: 0.8153 - precision: 0.7977 - recall: 0.7707 - auc: 0.8807 - prc: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.4915 - tp: 145238.0000 - fp: 36493.0000 - tn: 207196.0000 - fn: 42819.0000 - accuracy: 0.8163 - precision: 0.7992 - recall: 0.7723 - auc: 0.8816 - prc: 0.8962"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.4884 - tp: 147870.0000 - fp: 36778.0000 - tn: 209987.0000 - fn: 43255.0000 - accuracy: 0.8172 - precision: 0.8008 - recall: 0.7737 - auc: 0.8824 - prc: 0.8972"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.4852 - tp: 150543.0000 - fp: 37046.0000 - tn: 212781.0000 - fn: 43664.0000 - accuracy: 0.8182 - precision: 0.8025 - recall: 0.7752 - auc: 0.8833 - 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\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "192/278 [===================>..........] - ETA: 1s - loss: 0.4820 - tp: 153177.0000 - fp: 37328.0000 - tn: 215591.0000 - fn: 44082.0000 - accuracy: 0.8192 - precision: 0.8041 - recall: 0.7765 - auc: 0.8842 - prc: 0.8994"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4790 - tp: 155867.0000 - fp: 37593.0000 - tn: 218359.0000 - fn: 44503.0000 - accuracy: 0.8201 - precision: 0.8057 - recall: 0.7779 - auc: 0.8850 - prc: 0.9004"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4760 - tp: 158542.0000 - fp: 37866.0000 - tn: 221167.0000 - fn: 44891.0000 - accuracy: 0.8211 - precision: 0.8072 - recall: 0.7793 - auc: 0.8858 - prc: 0.9014"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4732 - tp: 161182.0000 - fp: 38154.0000 - tn: 223988.0000 - fn: 45286.0000 - accuracy: 0.8219 - precision: 0.8086 - recall: 0.7807 - auc: 0.8867 - prc: 0.9023"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4704 - tp: 163843.0000 - fp: 38426.0000 - tn: 226789.0000 - fn: 45696.0000 - accuracy: 0.8228 - precision: 0.8100 - recall: 0.7819 - auc: 0.8874 - prc: 0.9033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4676 - tp: 166550.0000 - fp: 38701.0000 - tn: 229552.0000 - fn: 46095.0000 - accuracy: 0.8237 - precision: 0.8114 - recall: 0.7832 - auc: 0.8883 - prc: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4646 - tp: 169273.0000 - fp: 38945.0000 - tn: 232336.0000 - fn: 46488.0000 - accuracy: 0.8246 - precision: 0.8130 - recall: 0.7845 - auc: 0.8891 - prc: 0.9053"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4619 - tp: 172020.0000 - fp: 39172.0000 - tn: 235088.0000 - fn: 46906.0000 - accuracy: 0.8255 - precision: 0.8145 - recall: 0.7857 - auc: 0.8899 - prc: 0.9062"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4593 - tp: 174642.0000 - fp: 39429.0000 - tn: 237941.0000 - fn: 47318.0000 - accuracy: 0.8263 - precision: 0.8158 - recall: 0.7868 - auc: 0.8906 - prc: 0.9070"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4566 - tp: 177380.0000 - fp: 39643.0000 - tn: 240758.0000 - fn: 47693.0000 - accuracy: 0.8272 - precision: 0.8173 - recall: 0.7881 - auc: 0.8915 - prc: 0.9080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4540 - tp: 180114.0000 - fp: 39880.0000 - tn: 243545.0000 - fn: 48079.0000 - accuracy: 0.8281 - precision: 0.8187 - recall: 0.7893 - auc: 0.8922 - prc: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4514 - tp: 182805.0000 - fp: 40105.0000 - tn: 246368.0000 - fn: 48484.0000 - accuracy: 0.8289 - precision: 0.8201 - recall: 0.7904 - auc: 0.8930 - prc: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4489 - tp: 185476.0000 - fp: 40297.0000 - tn: 249275.0000 - fn: 48858.0000 - accuracy: 0.8298 - precision: 0.8215 - recall: 0.7915 - auc: 0.8937 - prc: 0.9105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.4464 - tp: 188101.0000 - fp: 40524.0000 - tn: 252164.0000 - fn: 49261.0000 - accuracy: 0.8306 - precision: 0.8227 - recall: 0.7925 - auc: 0.8944 - prc: 0.9113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4439 - tp: 190810.0000 - fp: 40754.0000 - tn: 255006.0000 - fn: 49624.0000 - accuracy: 0.8314 - precision: 0.8240 - recall: 0.7936 - auc: 0.8952 - prc: 0.9121"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4415 - tp: 193516.0000 - fp: 40960.0000 - tn: 257839.0000 - fn: 50023.0000 - accuracy: 0.8322 - precision: 0.8253 - recall: 0.7946 - auc: 0.8959 - prc: 0.9128"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4391 - tp: 196236.0000 - fp: 41171.0000 - tn: 260660.0000 - fn: 50415.0000 - accuracy: 0.8330 - precision: 0.8266 - recall: 0.7956 - auc: 0.8966 - prc: 0.9136"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4369 - tp: 198961.0000 - fp: 41386.0000 - tn: 263464.0000 - fn: 50815.0000 - accuracy: 0.8338 - precision: 0.8278 - recall: 0.7966 - auc: 0.8973 - prc: 0.9144"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4345 - tp: 201663.0000 - fp: 41620.0000 - tn: 266306.0000 - fn: 51181.0000 - accuracy: 0.8345 - precision: 0.8289 - recall: 0.7976 - auc: 0.8980 - prc: 0.9151"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4323 - tp: 204337.0000 - fp: 41797.0000 - tn: 269222.0000 - fn: 51558.0000 - accuracy: 0.8353 - precision: 0.8302 - recall: 0.7985 - auc: 0.8987 - prc: 0.9158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4301 - tp: 207006.0000 - fp: 41996.0000 - tn: 272108.0000 - fn: 51948.0000 - accuracy: 0.8361 - precision: 0.8313 - recall: 0.7994 - auc: 0.8994 - prc: 0.9165"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4279 - tp: 209640.0000 - fp: 42194.0000 - tn: 275060.0000 - fn: 52308.0000 - accuracy: 0.8368 - precision: 0.8325 - recall: 0.8003 - auc: 0.9000 - prc: 0.9171"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4259 - tp: 212338.0000 - fp: 42394.0000 - tn: 277920.0000 - fn: 52694.0000 - accuracy: 0.8376 - precision: 0.8336 - recall: 0.8012 - auc: 0.9007 - prc: 0.9178"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4239 - tp: 215051.0000 - fp: 42600.0000 - tn: 280776.0000 - fn: 53063.0000 - accuracy: 0.8383 - precision: 0.8347 - recall: 0.8021 - auc: 0.9013 - prc: 0.9184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4218 - tp: 217737.0000 - fp: 42785.0000 - tn: 283673.0000 - fn: 53439.0000 - accuracy: 0.8390 - precision: 0.8358 - recall: 0.8029 - auc: 0.9019 - prc: 0.9191"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4197 - tp: 220426.0000 - fp: 42982.0000 - tn: 286562.0000 - fn: 53808.0000 - accuracy: 0.8397 - precision: 0.8368 - recall: 0.8038 - auc: 0.9026 - prc: 0.9197"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4177 - tp: 223099.0000 - fp: 43172.0000 - tn: 289466.0000 - fn: 54185.0000 - accuracy: 0.8404 - precision: 0.8379 - recall: 0.8046 - auc: 0.9032 - prc: 0.9203"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4158 - tp: 225796.0000 - fp: 43336.0000 - tn: 292390.0000 - fn: 54544.0000 - accuracy: 0.8411 - precision: 0.8390 - recall: 0.8054 - auc: 0.9038 - prc: 0.9209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4139 - tp: 228480.0000 - fp: 43527.0000 - tn: 295302.0000 - fn: 54901.0000 - accuracy: 0.8418 - precision: 0.8400 - recall: 0.8063 - auc: 0.9044 - prc: 0.9215"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 [==============================] - 8s 22ms/step - loss: 0.4126 - tp: 230239.0000 - fp: 43658.0000 - tn: 297273.0000 - fn: 55136.0000 - accuracy: 0.8423 - precision: 0.8406 - recall: 0.8068 - auc: 0.9048 - prc: 0.9219 - val_loss: 0.1683 - val_tp: 59.0000 - val_fp: 593.0000 - val_tn: 44907.0000 - val_fn: 10.0000 - val_accuracy: 0.9868 - val_precision: 0.0905 - val_recall: 0.8551 - val_auc: 0.9705 - val_prc: 0.6726\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 2s - loss: 0.2432 - tp: 919.0000 - fp: 61.0000 - tn: 938.0000 - fn: 130.0000 - accuracy: 0.9067 - precision: 0.9378 - recall: 0.8761 - auc: 0.9572 - prc: 0.9684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2384 - tp: 4562.0000 - fp: 309.0000 - tn: 4731.0000 - fn: 638.0000 - accuracy: 0.9075 - precision: 0.9366 - recall: 0.8773 - auc: 0.9584 - prc: 0.9695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.2346 - tp: 7322.0000 - fp: 485.0000 - tn: 7586.0000 - fn: 991.0000 - accuracy: 0.9099 - precision: 0.9379 - recall: 0.8808 - auc: 0.9596 - prc: 0.9707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2325 - tp: 10073.0000 - fp: 662.0000 - tn: 10451.0000 - fn: 1342.0000 - accuracy: 0.9110 - precision: 0.9383 - recall: 0.8824 - auc: 0.9603 - prc: 0.9712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2328 - tp: 12799.0000 - fp: 838.0000 - tn: 13326.0000 - fn: 1709.0000 - accuracy: 0.9112 - precision: 0.9385 - recall: 0.8822 - auc: 0.9602 - prc: 0.9710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2316 - tp: 15498.0000 - fp: 998.0000 - tn: 16243.0000 - fn: 2077.0000 - accuracy: 0.9117 - precision: 0.9395 - recall: 0.8818 - auc: 0.9606 - prc: 0.9712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2303 - tp: 18182.0000 - fp: 1163.0000 - tn: 19191.0000 - fn: 2424.0000 - accuracy: 0.9124 - precision: 0.9399 - recall: 0.8824 - auc: 0.9609 - prc: 0.9713"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2299 - tp: 20837.0000 - fp: 1355.0000 - tn: 22137.0000 - fn: 2775.0000 - accuracy: 0.9123 - precision: 0.9389 - recall: 0.8825 - auc: 0.9612 - prc: 0.9712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2297 - tp: 23519.0000 - fp: 1506.0000 - tn: 25084.0000 - fn: 3139.0000 - accuracy: 0.9128 - precision: 0.9398 - recall: 0.8822 - auc: 0.9611 - prc: 0.9712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2291 - tp: 26255.0000 - fp: 1687.0000 - tn: 27933.0000 - fn: 3517.0000 - accuracy: 0.9124 - precision: 0.9396 - recall: 0.8819 - auc: 0.9613 - 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\b\b\b\b\b\r",
      " 32/278 [==>...........................] - ETA: 5s - loss: 0.2288 - tp: 28996.0000 - fp: 1835.0000 - tn: 30835.0000 - fn: 3870.0000 - accuracy: 0.9129 - precision: 0.9405 - recall: 0.8822 - auc: 0.9613 - 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\b\b\b\b\b\r",
      " 35/278 [==>...........................] - ETA: 5s - loss: 0.2286 - tp: 31689.0000 - fp: 1983.0000 - tn: 33791.0000 - fn: 4217.0000 - accuracy: 0.9135 - precision: 0.9411 - recall: 0.8826 - auc: 0.9614 - 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\b\b\b\b\b\r",
      " 38/278 [===>..........................] - ETA: 4s - loss: 0.2285 - tp: 34377.0000 - fp: 2161.0000 - tn: 36696.0000 - fn: 4590.0000 - accuracy: 0.9133 - precision: 0.9409 - recall: 0.8822 - auc: 0.9614 - 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\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 4s - loss: 0.2280 - tp: 37080.0000 - fp: 2313.0000 - tn: 39610.0000 - fn: 4965.0000 - accuracy: 0.9133 - precision: 0.9413 - recall: 0.8819 - auc: 0.9616 - prc: 0.9715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.2271 - tp: 39809.0000 - fp: 2462.0000 - tn: 42537.0000 - fn: 5304.0000 - accuracy: 0.9138 - precision: 0.9418 - recall: 0.8824 - auc: 0.9618 - 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\b\b\b\b\b\r",
      " 47/278 [====>.........................] - ETA: 4s - loss: 0.2265 - tp: 42481.0000 - fp: 2613.0000 - tn: 45513.0000 - fn: 5649.0000 - accuracy: 0.9142 - precision: 0.9421 - recall: 0.8826 - auc: 0.9620 - 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\b\b\b\b\b\r",
      " 50/278 [====>.........................] - ETA: 4s - loss: 0.2265 - tp: 45163.0000 - fp: 2781.0000 - tn: 48448.0000 - fn: 6008.0000 - accuracy: 0.9142 - precision: 0.9420 - recall: 0.8826 - auc: 0.9619 - 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\b\b\b\b\b\r",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.2259 - tp: 47874.0000 - fp: 2943.0000 - tn: 51354.0000 - fn: 6373.0000 - accuracy: 0.9142 - precision: 0.9421 - recall: 0.8825 - auc: 0.9622 - 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\b\b\b\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.2254 - tp: 50548.0000 - fp: 3099.0000 - tn: 54316.0000 - fn: 6725.0000 - accuracy: 0.9143 - precision: 0.9422 - recall: 0.8826 - auc: 0.9624 - 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\b\b\b\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.2248 - tp: 53332.0000 - fp: 3253.0000 - tn: 57160.0000 - fn: 7087.0000 - accuracy: 0.9144 - precision: 0.9425 - recall: 0.8827 - auc: 0.9627 - 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\b\b\b\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.2244 - tp: 56134.0000 - fp: 3399.0000 - tn: 60014.0000 - fn: 7429.0000 - accuracy: 0.9147 - precision: 0.9429 - recall: 0.8831 - auc: 0.9628 - prc: 0.9723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2235 - tp: 58879.0000 - fp: 3520.0000 - tn: 62954.0000 - fn: 7767.0000 - accuracy: 0.9152 - precision: 0.9436 - recall: 0.8835 - auc: 0.9631 - prc: 0.9725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2231 - tp: 61608.0000 - fp: 3666.0000 - tn: 65876.0000 - fn: 8114.0000 - accuracy: 0.9154 - precision: 0.9438 - recall: 0.8836 - auc: 0.9633 - 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\b\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.2222 - tp: 64383.0000 - fp: 3823.0000 - tn: 68765.0000 - fn: 8437.0000 - accuracy: 0.9157 - precision: 0.9439 - recall: 0.8841 - auc: 0.9636 - prc: 0.9728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2214 - tp: 67126.0000 - fp: 3947.0000 - tn: 71692.0000 - fn: 8787.0000 - accuracy: 0.9160 - precision: 0.9445 - recall: 0.8842 - auc: 0.9638 - 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\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.2205 - tp: 69855.0000 - fp: 4079.0000 - tn: 74664.0000 - fn: 9098.0000 - accuracy: 0.9164 - precision: 0.9448 - recall: 0.8848 - auc: 0.9641 - 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\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.2199 - tp: 72640.0000 - fp: 4216.0000 - tn: 77538.0000 - fn: 9446.0000 - accuracy: 0.9166 - precision: 0.9451 - recall: 0.8849 - auc: 0.9644 - 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\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.2197 - tp: 75362.0000 - fp: 4353.0000 - tn: 80471.0000 - fn: 9798.0000 - accuracy: 0.9168 - precision: 0.9454 - recall: 0.8849 - auc: 0.9644 - 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\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 3s - loss: 0.2193 - tp: 78124.0000 - fp: 4480.0000 - tn: 83381.0000 - fn: 10143.0000 - accuracy: 0.9170 - precision: 0.9458 - recall: 0.8851 - auc: 0.9646 - prc: 0.9735"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.2189 - tp: 80817.0000 - fp: 4615.0000 - tn: 86372.0000 - fn: 10468.0000 - accuracy: 0.9173 - precision: 0.9460 - recall: 0.8853 - auc: 0.9648 - 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\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 3s - loss: 0.2184 - tp: 83554.0000 - fp: 4745.0000 - tn: 89287.0000 - fn: 10830.0000 - accuracy: 0.9173 - precision: 0.9463 - recall: 0.8853 - auc: 0.9649 - 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\b\b\b\b\r",
      " 95/278 [=========>....................] - ETA: 3s - loss: 0.2181 - tp: 86324.0000 - fp: 4889.0000 - tn: 92164.0000 - fn: 11183.0000 - accuracy: 0.9174 - precision: 0.9464 - recall: 0.8853 - auc: 0.9650 - 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\b\b\b\b\r",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.2178 - tp: 89048.0000 - fp: 5022.0000 - tn: 95108.0000 - fn: 11526.0000 - accuracy: 0.9176 - precision: 0.9466 - recall: 0.8854 - auc: 0.9652 - 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\b\b\b\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.2174 - tp: 91785.0000 - fp: 5156.0000 - tn: 98034.0000 - fn: 11873.0000 - accuracy: 0.9177 - precision: 0.9468 - recall: 0.8855 - auc: 0.9653 - 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\b\b\b\b\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.2172 - tp: 94525.0000 - fp: 5295.0000 - tn: 100953.0000 - fn: 12219.0000 - accuracy: 0.9178 - precision: 0.9470 - recall: 0.8855 - auc: 0.9654 - 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\b\b\b\b\b\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.2167 - tp: 97259.0000 - fp: 5431.0000 - tn: 103883.0000 - fn: 12563.0000 - accuracy: 0.9179 - precision: 0.9471 - recall: 0.8856 - auc: 0.9655 - prc: 0.9740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2162 - tp: 100016.0000 - fp: 5572.0000 - tn: 106799.0000 - fn: 12893.0000 - accuracy: 0.9180 - precision: 0.9472 - recall: 0.8858 - auc: 0.9657 - 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\b\b\b\b\b\b\r",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.2158 - tp: 102732.0000 - fp: 5702.0000 - tn: 109766.0000 - fn: 13224.0000 - accuracy: 0.9182 - precision: 0.9474 - recall: 0.8860 - auc: 0.9659 - 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\b\b\b\b\b\b\r",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.2152 - tp: 105436.0000 - fp: 5828.0000 - tn: 112759.0000 - fn: 13545.0000 - accuracy: 0.9185 - precision: 0.9476 - recall: 0.8862 - auc: 0.9660 - prc: 0.9743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2150 - tp: 108222.0000 - fp: 5960.0000 - tn: 115640.0000 - fn: 13890.0000 - accuracy: 0.9186 - precision: 0.9478 - recall: 0.8863 - auc: 0.9661 - prc: 0.9744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2146 - tp: 110972.0000 - fp: 6107.0000 - tn: 118548.0000 - fn: 14229.0000 - accuracy: 0.9186 - precision: 0.9478 - recall: 0.8864 - auc: 0.9663 - 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\b\b\b\b\b\b\r",
      "125/278 [============>.................] - ETA: 3s - loss: 0.2144 - tp: 113685.0000 - fp: 6259.0000 - tn: 121479.0000 - fn: 14577.0000 - accuracy: 0.9186 - precision: 0.9478 - recall: 0.8863 - auc: 0.9663 - 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\b\b\b\b\b\b\r",
      "128/278 [============>.................] - ETA: 3s - loss: 0.2141 - tp: 116403.0000 - fp: 6393.0000 - tn: 124444.0000 - fn: 14904.0000 - accuracy: 0.9188 - precision: 0.9479 - recall: 0.8865 - auc: 0.9665 - 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\b\b\b\b\b\b\r",
      "131/278 [=============>................] - ETA: 3s - loss: 0.2140 - tp: 119161.0000 - fp: 6537.0000 - tn: 127337.0000 - fn: 15253.0000 - accuracy: 0.9188 - precision: 0.9480 - recall: 0.8865 - auc: 0.9665 - 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\b\b\b\b\b\b\r",
      "134/278 [=============>................] - ETA: 2s - loss: 0.2136 - tp: 121892.0000 - fp: 6664.0000 - tn: 130284.0000 - fn: 15592.0000 - accuracy: 0.9189 - precision: 0.9482 - recall: 0.8866 - auc: 0.9666 - prc: 0.9747"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.2133 - tp: 124597.0000 - fp: 6794.0000 - tn: 133266.0000 - fn: 15919.0000 - accuracy: 0.9190 - precision: 0.9483 - recall: 0.8867 - auc: 0.9667 - 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\b\b\b\b\b\b\r",
      "140/278 [==============>...............] - ETA: 2s - loss: 0.2129 - tp: 127285.0000 - fp: 6924.0000 - tn: 136275.0000 - fn: 16236.0000 - accuracy: 0.9192 - precision: 0.9484 - recall: 0.8869 - auc: 0.9668 - 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\b\b\b\b\b\b\r",
      "143/278 [==============>...............] - ETA: 2s - loss: 0.2126 - tp: 130034.0000 - fp: 7070.0000 - tn: 139189.0000 - fn: 16571.0000 - accuracy: 0.9193 - precision: 0.9484 - recall: 0.8870 - auc: 0.9670 - 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\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.2121 - tp: 132772.0000 - fp: 7189.0000 - tn: 142170.0000 - fn: 16877.0000 - accuracy: 0.9195 - precision: 0.9486 - recall: 0.8872 - auc: 0.9671 - 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\b\b\b\r",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.2117 - tp: 135527.0000 - fp: 7333.0000 - tn: 145107.0000 - fn: 17185.0000 - accuracy: 0.9197 - precision: 0.9487 - recall: 0.8875 - auc: 0.9673 - 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\b\b\b\r",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.2113 - tp: 138251.0000 - fp: 7468.0000 - tn: 148059.0000 - fn: 17518.0000 - accuracy: 0.9197 - precision: 0.9488 - recall: 0.8875 - auc: 0.9674 - 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\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.2110 - tp: 141003.0000 - fp: 7601.0000 - tn: 150991.0000 - fn: 17845.0000 - accuracy: 0.9198 - precision: 0.9489 - recall: 0.8877 - auc: 0.9675 - 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\b\b\b\b\b\b\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.2106 - tp: 143801.0000 - fp: 7718.0000 - tn: 153882.0000 - fn: 18183.0000 - accuracy: 0.9200 - precision: 0.9491 - recall: 0.8877 - auc: 0.9676 - 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\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.2103 - tp: 146524.0000 - fp: 7850.0000 - tn: 156828.0000 - fn: 18526.0000 - accuracy: 0.9200 - precision: 0.9491 - recall: 0.8878 - auc: 0.9677 - 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\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.2100 - tp: 149282.0000 - fp: 7980.0000 - tn: 159754.0000 - fn: 18856.0000 - accuracy: 0.9201 - precision: 0.9493 - recall: 0.8879 - auc: 0.9678 - 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\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.2096 - tp: 151999.0000 - fp: 8104.0000 - tn: 162728.0000 - fn: 19185.0000 - accuracy: 0.9202 - precision: 0.9494 - recall: 0.8879 - auc: 0.9679 - 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\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.2093 - tp: 154740.0000 - fp: 8232.0000 - tn: 165687.0000 - fn: 19501.0000 - accuracy: 0.9203 - precision: 0.9495 - recall: 0.8881 - auc: 0.9680 - 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\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.2090 - tp: 157464.0000 - fp: 8362.0000 - tn: 168657.0000 - fn: 19821.0000 - accuracy: 0.9205 - precision: 0.9496 - recall: 0.8882 - auc: 0.9681 - 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\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.2085 - tp: 160165.0000 - fp: 8474.0000 - tn: 171676.0000 - fn: 20133.0000 - accuracy: 0.9206 - precision: 0.9498 - recall: 0.8883 - auc: 0.9683 - 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\b\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.2081 - tp: 162910.0000 - fp: 8594.0000 - tn: 174630.0000 - fn: 20458.0000 - accuracy: 0.9208 - precision: 0.9499 - recall: 0.8884 - auc: 0.9684 - 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\b\b\b\r",
      "182/278 [==================>...........] - ETA: 2s - loss: 0.2077 - tp: 165687.0000 - fp: 8704.0000 - tn: 177577.0000 - fn: 20768.0000 - accuracy: 0.9209 - precision: 0.9501 - recall: 0.8886 - auc: 0.9686 - 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\b\b\b\b\r",
      "185/278 [==================>...........] - ETA: 1s - loss: 0.2074 - tp: 168462.0000 - fp: 8825.0000 - tn: 180510.0000 - fn: 21083.0000 - accuracy: 0.9211 - precision: 0.9502 - recall: 0.8888 - auc: 0.9687 - 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\b\b\b\r",
      "188/278 [===================>..........] - ETA: 1s - loss: 0.2070 - tp: 171289.0000 - fp: 8951.0000 - tn: 183386.0000 - fn: 21398.0000 - accuracy: 0.9212 - precision: 0.9503 - recall: 0.8889 - auc: 0.9688 - 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\b\b\b\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.2067 - tp: 173992.0000 - fp: 9059.0000 - tn: 186398.0000 - fn: 21719.0000 - accuracy: 0.9213 - precision: 0.9505 - recall: 0.8890 - auc: 0.9689 - 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\b\b\b\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.2064 - tp: 176739.0000 - fp: 9182.0000 - tn: 189348.0000 - fn: 22043.0000 - accuracy: 0.9214 - precision: 0.9506 - recall: 0.8891 - auc: 0.9690 - 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\b\b\b\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.2061 - tp: 179449.0000 - fp: 9299.0000 - tn: 192333.0000 - fn: 22375.0000 - accuracy: 0.9215 - precision: 0.9507 - recall: 0.8891 - auc: 0.9691 - 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\b\b\b\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.2058 - tp: 182241.0000 - fp: 9427.0000 - tn: 195237.0000 - fn: 22695.0000 - accuracy: 0.9216 - precision: 0.9508 - recall: 0.8893 - auc: 0.9692 - 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\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.2056 - tp: 184106.0000 - fp: 9503.0000 - tn: 197187.0000 - fn: 22900.0000 - accuracy: 0.9217 - precision: 0.9509 - recall: 0.8894 - auc: 0.9692 - 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\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.2051 - tp: 186840.0000 - fp: 9621.0000 - tn: 200169.0000 - fn: 23210.0000 - accuracy: 0.9218 - precision: 0.9510 - recall: 0.8895 - auc: 0.9694 - 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\b\b\r",
      "207/278 [=====================>........] - ETA: 1s - loss: 0.2050 - tp: 188639.0000 - fp: 9707.0000 - tn: 202164.0000 - fn: 23426.0000 - accuracy: 0.9218 - precision: 0.9511 - recall: 0.8895 - auc: 0.9695 - 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\b\b\r",
      "210/278 [=====================>........] - ETA: 1s - loss: 0.2047 - tp: 191463.0000 - fp: 9809.0000 - tn: 205076.0000 - fn: 23732.0000 - accuracy: 0.9220 - precision: 0.9513 - recall: 0.8897 - auc: 0.9696 - 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\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.2044 - tp: 194206.0000 - fp: 9917.0000 - tn: 208034.0000 - fn: 24067.0000 - accuracy: 0.9221 - precision: 0.9514 - recall: 0.8897 - auc: 0.9696 - 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\b\b\r",
      "216/278 [======================>.......] - ETA: 1s - loss: 0.2043 - tp: 196956.0000 - fp: 10048.0000 - tn: 210963.0000 - fn: 24401.0000 - accuracy: 0.9221 - precision: 0.9515 - recall: 0.8898 - auc: 0.9697 - 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\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.2040 - tp: 199720.0000 - fp: 10179.0000 - tn: 213907.0000 - fn: 24706.0000 - accuracy: 0.9222 - precision: 0.9515 - recall: 0.8899 - auc: 0.9698 - 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\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.2038 - tp: 202406.0000 - fp: 10272.0000 - tn: 216938.0000 - fn: 25040.0000 - accuracy: 0.9223 - precision: 0.9517 - recall: 0.8899 - auc: 0.9699 - 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\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.2034 - tp: 205137.0000 - fp: 10402.0000 - tn: 219924.0000 - fn: 25337.0000 - accuracy: 0.9224 - precision: 0.9517 - recall: 0.8901 - auc: 0.9700 - 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\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.2030 - tp: 207910.0000 - fp: 10506.0000 - tn: 222879.0000 - fn: 25649.0000 - accuracy: 0.9226 - precision: 0.9519 - recall: 0.8902 - auc: 0.9701 - 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\b\b\b\r",
      "231/278 [=======================>......] - ETA: 0s - loss: 0.2028 - tp: 210640.0000 - fp: 10634.0000 - tn: 225856.0000 - fn: 25958.0000 - accuracy: 0.9227 - precision: 0.9519 - recall: 0.8903 - auc: 0.9702 - 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\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.2024 - tp: 213423.0000 - fp: 10754.0000 - tn: 228800.0000 - fn: 26255.0000 - accuracy: 0.9228 - precision: 0.9520 - recall: 0.8905 - auc: 0.9703 - 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\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.2022 - tp: 216176.0000 - fp: 10871.0000 - tn: 231778.0000 - fn: 26551.0000 - accuracy: 0.9229 - precision: 0.9521 - recall: 0.8906 - auc: 0.9704 - 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\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.2018 - tp: 218905.0000 - fp: 10982.0000 - tn: 234786.0000 - fn: 26847.0000 - accuracy: 0.9230 - precision: 0.9522 - recall: 0.8908 - auc: 0.9705 - 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\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.2015 - tp: 221691.0000 - fp: 11098.0000 - tn: 237713.0000 - fn: 27162.0000 - accuracy: 0.9231 - precision: 0.9523 - recall: 0.8909 - auc: 0.9706 - 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\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.2013 - tp: 224506.0000 - fp: 11218.0000 - tn: 240617.0000 - fn: 27467.0000 - accuracy: 0.9232 - precision: 0.9524 - recall: 0.8910 - auc: 0.9707 - 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\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.2010 - tp: 227291.0000 - fp: 11334.0000 - tn: 243551.0000 - fn: 27776.0000 - accuracy: 0.9233 - precision: 0.9525 - recall: 0.8911 - auc: 0.9708 - 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\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.2007 - tp: 230060.0000 - fp: 11450.0000 - tn: 246519.0000 - fn: 28067.0000 - accuracy: 0.9234 - precision: 0.9526 - recall: 0.8913 - auc: 0.9709 - 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\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.2005 - tp: 232868.0000 - fp: 11600.0000 - tn: 249389.0000 - fn: 28383.0000 - accuracy: 0.9234 - precision: 0.9526 - recall: 0.8914 - auc: 0.9710 - 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\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.2002 - tp: 235655.0000 - fp: 11710.0000 - tn: 252330.0000 - fn: 28689.0000 - accuracy: 0.9235 - precision: 0.9527 - recall: 0.8915 - auc: 0.9711 - 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\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1999 - tp: 238440.0000 - fp: 11813.0000 - tn: 255273.0000 - fn: 29002.0000 - accuracy: 0.9236 - precision: 0.9528 - recall: 0.8916 - auc: 0.9712 - 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\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1997 - tp: 241238.0000 - fp: 11928.0000 - tn: 258193.0000 - fn: 29313.0000 - accuracy: 0.9237 - precision: 0.9529 - recall: 0.8917 - auc: 0.9712 - 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\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1994 - tp: 244024.0000 - fp: 12040.0000 - tn: 261133.0000 - fn: 29619.0000 - accuracy: 0.9238 - precision: 0.9530 - recall: 0.8918 - auc: 0.9713 - 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\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1992 - tp: 246779.0000 - fp: 12162.0000 - tn: 264102.0000 - fn: 29917.0000 - accuracy: 0.9239 - precision: 0.9530 - recall: 0.8919 - auc: 0.9714 - 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\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1989 - tp: 249561.0000 - fp: 12255.0000 - tn: 267065.0000 - fn: 30223.0000 - accuracy: 0.9240 - precision: 0.9532 - recall: 0.8920 - auc: 0.9715 - 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\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1986 - tp: 252381.0000 - fp: 12355.0000 - tn: 269995.0000 - fn: 30517.0000 - accuracy: 0.9242 - precision: 0.9533 - recall: 0.8921 - auc: 0.9716 - 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\b\r",
      "278/278 [==============================] - 6s 22ms/step - loss: 0.1984 - tp: 254251.0000 - fp: 12432.0000 - tn: 271931.0000 - fn: 30730.0000 - accuracy: 0.9242 - precision: 0.9534 - recall: 0.8922 - auc: 0.9716 - prc: 0.9779 - val_loss: 0.0992 - val_tp: 59.0000 - val_fp: 605.0000 - val_tn: 44895.0000 - val_fn: 10.0000 - val_accuracy: 0.9865 - val_precision: 0.0889 - val_recall: 0.8551 - val_auc: 0.9667 - val_prc: 0.6655\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1696 - tp: 954.0000 - fp: 37.0000 - tn: 951.0000 - fn: 106.0000 - accuracy: 0.9302 - precision: 0.9627 - recall: 0.9000 - auc: 0.9799 - 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\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1711 - tp: 4591.0000 - fp: 178.0000 - tn: 4937.0000 - fn: 534.0000 - accuracy: 0.9305 - precision: 0.9627 - recall: 0.8958 - auc: 0.9794 - 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\r",
      "  8/278 [..............................] - ETA: 4s - loss: 0.1716 - tp: 7391.0000 - fp: 295.0000 - tn: 7882.0000 - fn: 816.0000 - accuracy: 0.9322 - precision: 0.9616 - recall: 0.9006 - auc: 0.9795 - 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\r",
      " 11/278 [>.............................] - ETA: 4s - loss: 0.1728 - tp: 10181.0000 - fp: 419.0000 - tn: 10808.0000 - fn: 1120.0000 - accuracy: 0.9317 - precision: 0.9605 - recall: 0.9009 - auc: 0.9792 - 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\r",
      " 14/278 [>.............................] - ETA: 4s - loss: 0.1707 - tp: 12930.0000 - fp: 513.0000 - tn: 13814.0000 - fn: 1415.0000 - accuracy: 0.9328 - precision: 0.9618 - recall: 0.9014 - auc: 0.9799 - 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\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1705 - tp: 15751.0000 - fp: 618.0000 - tn: 16731.0000 - fn: 1716.0000 - accuracy: 0.9330 - precision: 0.9622 - recall: 0.9018 - auc: 0.9797 - 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\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1706 - tp: 18562.0000 - fp: 729.0000 - tn: 19656.0000 - fn: 2013.0000 - accuracy: 0.9331 - precision: 0.9622 - recall: 0.9022 - auc: 0.9797 - 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\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1703 - tp: 21361.0000 - fp: 827.0000 - tn: 22590.0000 - fn: 2326.0000 - accuracy: 0.9331 - precision: 0.9627 - recall: 0.9018 - auc: 0.9798 - 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\r",
      " 26/278 [=>............................] - ETA: 4s - loss: 0.1704 - tp: 24133.0000 - fp: 924.0000 - tn: 25559.0000 - fn: 2632.0000 - accuracy: 0.9332 - precision: 0.9631 - recall: 0.9017 - auc: 0.9798 - 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\r",
      " 29/278 [==>...........................] - ETA: 4s - loss: 0.1709 - tp: 26974.0000 - fp: 1046.0000 - tn: 28463.0000 - fn: 2909.0000 - accuracy: 0.9334 - precision: 0.9627 - recall: 0.9027 - auc: 0.9797 - 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",
      " 32/278 [==>...........................] - ETA: 4s - loss: 0.1715 - tp: 29757.0000 - fp: 1167.0000 - tn: 31404.0000 - fn: 3208.0000 - accuracy: 0.9332 - precision: 0.9623 - recall: 0.9027 - auc: 0.9796 - 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",
      " 35/278 [==>...........................] - ETA: 4s - loss: 0.1716 - tp: 32464.0000 - fp: 1274.0000 - tn: 34423.0000 - fn: 3519.0000 - accuracy: 0.9331 - precision: 0.9622 - recall: 0.9022 - auc: 0.9796 - 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",
      " 38/278 [===>..........................] - ETA: 4s - loss: 0.1714 - tp: 35257.0000 - fp: 1372.0000 - tn: 37359.0000 - fn: 3836.0000 - accuracy: 0.9331 - precision: 0.9625 - recall: 0.9019 - auc: 0.9797 - 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",
      " 41/278 [===>..........................] - ETA: 4s - loss: 0.1710 - tp: 38021.0000 - fp: 1467.0000 - tn: 40364.0000 - fn: 4116.0000 - accuracy: 0.9335 - precision: 0.9628 - recall: 0.9023 - auc: 0.9797 - 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",
      " 44/278 [===>..........................] - ETA: 4s - loss: 0.1710 - tp: 40812.0000 - fp: 1592.0000 - tn: 43305.0000 - fn: 4403.0000 - accuracy: 0.9335 - precision: 0.9625 - recall: 0.9026 - auc: 0.9798 - 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",
      " 47/278 [====>.........................] - ETA: 4s - loss: 0.1709 - tp: 43567.0000 - fp: 1690.0000 - tn: 46309.0000 - fn: 4690.0000 - accuracy: 0.9337 - precision: 0.9627 - recall: 0.9028 - auc: 0.9798 - 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",
      " 50/278 [====>.........................] - ETA: 4s - loss: 0.1711 - tp: 46346.0000 - fp: 1797.0000 - tn: 49262.0000 - fn: 4995.0000 - accuracy: 0.9337 - precision: 0.9627 - recall: 0.9027 - auc: 0.9798 - 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",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.1712 - tp: 49122.0000 - fp: 1916.0000 - tn: 52197.0000 - fn: 5309.0000 - accuracy: 0.9334 - precision: 0.9625 - recall: 0.9025 - auc: 0.9798 - 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",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1714 - tp: 51890.0000 - fp: 2032.0000 - tn: 55147.0000 - fn: 5619.0000 - accuracy: 0.9333 - precision: 0.9623 - recall: 0.9023 - auc: 0.9797 - 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",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1710 - tp: 54662.0000 - fp: 2127.0000 - tn: 58126.0000 - fn: 5917.0000 - accuracy: 0.9334 - precision: 0.9625 - recall: 0.9023 - auc: 0.9798 - 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",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1706 - tp: 57458.0000 - fp: 2240.0000 - tn: 61094.0000 - fn: 6184.0000 - accuracy: 0.9337 - precision: 0.9625 - recall: 0.9028 - auc: 0.9799 - 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",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.1706 - tp: 60262.0000 - fp: 2350.0000 - tn: 64020.0000 - fn: 6488.0000 - accuracy: 0.9336 - precision: 0.9625 - recall: 0.9028 - auc: 0.9799 - 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",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1703 - tp: 63100.0000 - fp: 2458.0000 - tn: 66934.0000 - fn: 6772.0000 - accuracy: 0.9337 - precision: 0.9625 - recall: 0.9031 - auc: 0.9800 - 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",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1702 - tp: 65814.0000 - fp: 2562.0000 - tn: 69969.0000 - fn: 7063.0000 - accuracy: 0.9338 - precision: 0.9625 - recall: 0.9031 - auc: 0.9800 - 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",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1698 - tp: 68591.0000 - fp: 2669.0000 - tn: 72948.0000 - fn: 7344.0000 - accuracy: 0.9339 - precision: 0.9625 - recall: 0.9033 - auc: 0.9801 - 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",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.1696 - tp: 71386.0000 - fp: 2763.0000 - tn: 75915.0000 - fn: 7632.0000 - accuracy: 0.9341 - precision: 0.9627 - recall: 0.9034 - auc: 0.9801 - 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",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1695 - tp: 74164.0000 - fp: 2865.0000 - tn: 78868.0000 - fn: 7943.0000 - accuracy: 0.9340 - precision: 0.9628 - recall: 0.9033 - auc: 0.9802 - 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",
      " 83/278 [=======>......................] - ETA: 4s - loss: 0.1694 - tp: 76892.0000 - fp: 2986.0000 - tn: 81870.0000 - fn: 8236.0000 - accuracy: 0.9340 - precision: 0.9626 - recall: 0.9033 - auc: 0.9802 - 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",
      " 86/278 [========>.....................] - ETA: 3s - loss: 0.1695 - tp: 79685.0000 - fp: 3105.0000 - tn: 84808.0000 - fn: 8530.0000 - accuracy: 0.9339 - precision: 0.9625 - recall: 0.9033 - auc: 0.9802 - 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",
      " 89/278 [========>.....................] - ETA: 3s - loss: 0.1693 - tp: 82437.0000 - fp: 3200.0000 - tn: 87810.0000 - fn: 8825.0000 - accuracy: 0.9340 - precision: 0.9626 - recall: 0.9033 - auc: 0.9803 - 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",
      " 92/278 [========>.....................] - ETA: 3s - loss: 0.1691 - tp: 85177.0000 - fp: 3296.0000 - tn: 90814.0000 - fn: 9129.0000 - accuracy: 0.9341 - precision: 0.9627 - recall: 0.9032 - auc: 0.9803 - 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\r",
      " 95/278 [=========>....................] - ETA: 3s - loss: 0.1688 - tp: 87997.0000 - fp: 3380.0000 - tn: 93744.0000 - fn: 9439.0000 - accuracy: 0.9341 - precision: 0.9630 - recall: 0.9031 - auc: 0.9804 - 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\r",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.1688 - tp: 90794.0000 - fp: 3483.0000 - tn: 96694.0000 - fn: 9733.0000 - accuracy: 0.9342 - precision: 0.9631 - recall: 0.9032 - auc: 0.9804 - 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\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1687 - tp: 93578.0000 - fp: 3591.0000 - tn: 99668.0000 - fn: 10011.0000 - accuracy: 0.9342 - precision: 0.9630 - recall: 0.9034 - auc: 0.9804 - 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\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1683 - tp: 96348.0000 - fp: 3680.0000 - tn: 102662.0000 - fn: 10302.0000 - accuracy: 0.9344 - precision: 0.9632 - recall: 0.9034 - auc: 0.9805 - 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\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1681 - tp: 99126.0000 - fp: 3773.0000 - tn: 105635.0000 - fn: 10602.0000 - accuracy: 0.9344 - precision: 0.9633 - recall: 0.9034 - auc: 0.9806 - 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\r",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1679 - tp: 101895.0000 - fp: 3878.0000 - tn: 108607.0000 - fn: 10900.0000 - accuracy: 0.9344 - precision: 0.9633 - recall: 0.9034 - auc: 0.9806 - 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",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1677 - tp: 104675.0000 - fp: 3975.0000 - tn: 111588.0000 - fn: 11186.0000 - accuracy: 0.9345 - precision: 0.9634 - recall: 0.9035 - auc: 0.9807 - 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",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1676 - tp: 107440.0000 - fp: 4061.0000 - tn: 114597.0000 - fn: 11470.0000 - accuracy: 0.9346 - precision: 0.9636 - recall: 0.9035 - auc: 0.9807 - 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",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1676 - tp: 110237.0000 - fp: 4159.0000 - tn: 117546.0000 - fn: 11770.0000 - accuracy: 0.9346 - precision: 0.9636 - recall: 0.9035 - auc: 0.9807 - 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",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1673 - tp: 113064.0000 - fp: 4247.0000 - tn: 120489.0000 - fn: 12056.0000 - accuracy: 0.9348 - precision: 0.9638 - recall: 0.9036 - auc: 0.9808 - 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",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1672 - tp: 115858.0000 - fp: 4346.0000 - tn: 123422.0000 - fn: 12374.0000 - accuracy: 0.9347 - precision: 0.9638 - recall: 0.9035 - auc: 0.9808 - 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",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1670 - tp: 118690.0000 - fp: 4442.0000 - tn: 126354.0000 - fn: 12658.0000 - accuracy: 0.9348 - precision: 0.9639 - recall: 0.9036 - auc: 0.9808 - 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",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1668 - tp: 121479.0000 - fp: 4537.0000 - tn: 129325.0000 - fn: 12947.0000 - accuracy: 0.9348 - precision: 0.9640 - recall: 0.9037 - auc: 0.9809 - 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",
      "134/278 [=============>................] - ETA: 2s - loss: 0.1668 - tp: 124191.0000 - fp: 4646.0000 - tn: 132351.0000 - fn: 13244.0000 - accuracy: 0.9348 - precision: 0.9639 - recall: 0.9036 - auc: 0.9809 - 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",
      "137/278 [=============>................] - ETA: 2s - loss: 0.1667 - tp: 126923.0000 - fp: 4751.0000 - tn: 135361.0000 - fn: 13541.0000 - accuracy: 0.9348 - precision: 0.9639 - recall: 0.9036 - auc: 0.9810 - 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",
      "140/278 [==============>...............] - ETA: 2s - loss: 0.1666 - tp: 129712.0000 - fp: 4853.0000 - tn: 138333.0000 - fn: 13822.0000 - accuracy: 0.9349 - precision: 0.9639 - recall: 0.9037 - auc: 0.9810 - 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",
      "143/278 [==============>...............] - ETA: 2s - loss: 0.1664 - tp: 132472.0000 - fp: 4963.0000 - tn: 141316.0000 - fn: 14113.0000 - accuracy: 0.9349 - precision: 0.9639 - recall: 0.9037 - auc: 0.9810 - 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",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.1661 - tp: 135276.0000 - fp: 5049.0000 - tn: 144285.0000 - fn: 14398.0000 - accuracy: 0.9350 - precision: 0.9640 - recall: 0.9038 - auc: 0.9811 - 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",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.1659 - tp: 138141.0000 - fp: 5164.0000 - tn: 147171.0000 - fn: 14676.0000 - accuracy: 0.9350 - precision: 0.9640 - recall: 0.9040 - auc: 0.9811 - 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",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1658 - tp: 140923.0000 - fp: 5265.0000 - tn: 150136.0000 - fn: 14972.0000 - accuracy: 0.9350 - precision: 0.9640 - recall: 0.9040 - auc: 0.9812 - 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\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1656 - tp: 143671.0000 - fp: 5362.0000 - tn: 153144.0000 - fn: 15263.0000 - accuracy: 0.9350 - precision: 0.9640 - recall: 0.9040 - auc: 0.9812 - 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\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1653 - tp: 146479.0000 - fp: 5454.0000 - tn: 156113.0000 - fn: 15538.0000 - accuracy: 0.9351 - precision: 0.9641 - recall: 0.9041 - auc: 0.9813 - 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\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1652 - tp: 149256.0000 - fp: 5578.0000 - tn: 159069.0000 - fn: 15825.0000 - accuracy: 0.9351 - precision: 0.9640 - recall: 0.9041 - auc: 0.9813 - 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\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1650 - tp: 152150.0000 - fp: 5668.0000 - tn: 161930.0000 - fn: 16124.0000 - accuracy: 0.9351 - precision: 0.9641 - recall: 0.9042 - auc: 0.9814 - 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\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1649 - tp: 155019.0000 - fp: 5754.0000 - tn: 164823.0000 - fn: 16420.0000 - accuracy: 0.9352 - precision: 0.9642 - recall: 0.9042 - auc: 0.9814 - 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\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1647 - tp: 157773.0000 - fp: 5846.0000 - tn: 167851.0000 - fn: 16690.0000 - accuracy: 0.9353 - precision: 0.9643 - recall: 0.9043 - auc: 0.9815 - 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\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1645 - tp: 160565.0000 - fp: 5949.0000 - tn: 170837.0000 - fn: 16953.0000 - accuracy: 0.9354 - precision: 0.9643 - recall: 0.9045 - auc: 0.9815 - 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\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1643 - tp: 163384.0000 - fp: 6062.0000 - tn: 173768.0000 - fn: 17234.0000 - accuracy: 0.9354 - precision: 0.9642 - recall: 0.9046 - auc: 0.9816 - 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\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1642 - tp: 166129.0000 - fp: 6169.0000 - tn: 176776.0000 - fn: 17518.0000 - accuracy: 0.9354 - precision: 0.9642 - recall: 0.9046 - auc: 0.9816 - 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\r",
      "182/278 [==================>...........] - ETA: 1s - loss: 0.1640 - tp: 168926.0000 - fp: 6268.0000 - tn: 179744.0000 - fn: 17798.0000 - accuracy: 0.9354 - precision: 0.9642 - recall: 0.9047 - auc: 0.9817 - 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\r",
      "185/278 [==================>...........] - ETA: 1s - loss: 0.1638 - tp: 171759.0000 - fp: 6364.0000 - tn: 182659.0000 - fn: 18098.0000 - accuracy: 0.9354 - precision: 0.9643 - recall: 0.9047 - auc: 0.9817 - 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\r",
      "188/278 [===================>..........] - ETA: 1s - loss: 0.1637 - tp: 174558.0000 - fp: 6463.0000 - tn: 185631.0000 - fn: 18372.0000 - accuracy: 0.9355 - precision: 0.9643 - recall: 0.9048 - auc: 0.9818 - 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\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1635 - tp: 177306.0000 - fp: 6564.0000 - tn: 188635.0000 - fn: 18663.0000 - accuracy: 0.9355 - precision: 0.9643 - recall: 0.9048 - auc: 0.9818 - 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\r",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1633 - tp: 180108.0000 - fp: 6656.0000 - tn: 191621.0000 - fn: 18927.0000 - accuracy: 0.9356 - precision: 0.9644 - recall: 0.9049 - auc: 0.9819 - 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\r",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.1632 - tp: 182965.0000 - fp: 6758.0000 - tn: 194522.0000 - fn: 19211.0000 - accuracy: 0.9356 - precision: 0.9644 - recall: 0.9050 - auc: 0.9819 - 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\r",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.1631 - tp: 185807.0000 - fp: 6875.0000 - tn: 197410.0000 - fn: 19508.0000 - accuracy: 0.9356 - precision: 0.9643 - recall: 0.9050 - auc: 0.9819 - 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\r",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.1630 - tp: 188663.0000 - fp: 6969.0000 - tn: 200326.0000 - fn: 19786.0000 - accuracy: 0.9356 - precision: 0.9644 - recall: 0.9051 - auc: 0.9820 - 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\r",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.1628 - tp: 191458.0000 - fp: 7074.0000 - tn: 203295.0000 - fn: 20061.0000 - accuracy: 0.9357 - precision: 0.9644 - recall: 0.9052 - auc: 0.9820 - 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\r",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1627 - tp: 194230.0000 - fp: 7157.0000 - tn: 206294.0000 - fn: 20351.0000 - accuracy: 0.9357 - precision: 0.9645 - recall: 0.9052 - auc: 0.9821 - 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\r",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1626 - tp: 197033.0000 - fp: 7251.0000 - tn: 209259.0000 - fn: 20633.0000 - accuracy: 0.9358 - precision: 0.9645 - recall: 0.9052 - auc: 0.9821 - 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\r",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1625 - tp: 199864.0000 - fp: 7374.0000 - tn: 212195.0000 - fn: 20887.0000 - accuracy: 0.9358 - precision: 0.9644 - recall: 0.9054 - auc: 0.9821 - 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\r",
      "218/278 [======================>.......] - ETA: 1s - loss: 0.1623 - tp: 202627.0000 - fp: 7483.0000 - tn: 215192.0000 - fn: 21162.0000 - accuracy: 0.9358 - precision: 0.9644 - recall: 0.9054 - auc: 0.9822 - prc: 0.9852"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1621 - tp: 205424.0000 - fp: 7580.0000 - tn: 218182.0000 - fn: 21422.0000 - accuracy: 0.9359 - precision: 0.9644 - recall: 0.9056 - auc: 0.9822 - prc: 0.9852"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1621 - tp: 208195.0000 - fp: 7679.0000 - tn: 221148.0000 - fn: 21730.0000 - accuracy: 0.9359 - precision: 0.9644 - recall: 0.9055 - auc: 0.9822 - prc: 0.9852"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1619 - tp: 210945.0000 - fp: 7779.0000 - tn: 224167.0000 - fn: 22005.0000 - accuracy: 0.9359 - precision: 0.9644 - recall: 0.9055 - auc: 0.9823 - prc: 0.9852"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.1617 - tp: 213753.0000 - fp: 7872.0000 - tn: 227121.0000 - fn: 22294.0000 - accuracy: 0.9360 - precision: 0.9645 - recall: 0.9056 - auc: 0.9823 - prc: 0.9853"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.1616 - tp: 216547.0000 - fp: 7960.0000 - tn: 230089.0000 - fn: 22588.0000 - accuracy: 0.9360 - precision: 0.9645 - recall: 0.9055 - auc: 0.9824 - prc: 0.9853"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1614 - tp: 219340.0000 - fp: 8056.0000 - tn: 233063.0000 - fn: 22869.0000 - accuracy: 0.9360 - precision: 0.9646 - recall: 0.9056 - auc: 0.9824 - prc: 0.9853"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1613 - tp: 222149.0000 - fp: 8153.0000 - tn: 236019.0000 - fn: 23151.0000 - accuracy: 0.9360 - precision: 0.9646 - recall: 0.9056 - auc: 0.9824 - prc: 0.9853"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1612 - tp: 224974.0000 - fp: 8255.0000 - tn: 238975.0000 - fn: 23412.0000 - accuracy: 0.9361 - precision: 0.9646 - recall: 0.9057 - auc: 0.9825 - prc: 0.9854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1610 - tp: 227799.0000 - fp: 8342.0000 - tn: 241938.0000 - fn: 23681.0000 - accuracy: 0.9362 - precision: 0.9647 - recall: 0.9058 - auc: 0.9825 - prc: 0.9854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1609 - tp: 230627.0000 - fp: 8435.0000 - tn: 244868.0000 - fn: 23974.0000 - accuracy: 0.9362 - precision: 0.9647 - recall: 0.9058 - auc: 0.9825 - prc: 0.9854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1609 - tp: 233459.0000 - fp: 8533.0000 - tn: 247802.0000 - fn: 24254.0000 - accuracy: 0.9362 - precision: 0.9647 - recall: 0.9059 - auc: 0.9825 - prc: 0.9854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1608 - tp: 236299.0000 - fp: 8635.0000 - tn: 250738.0000 - fn: 24520.0000 - accuracy: 0.9363 - precision: 0.9647 - recall: 0.9060 - auc: 0.9826 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1607 - tp: 239106.0000 - fp: 8731.0000 - tn: 253684.0000 - fn: 24815.0000 - accuracy: 0.9363 - precision: 0.9648 - recall: 0.9060 - auc: 0.9826 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1606 - tp: 241887.0000 - fp: 8824.0000 - tn: 256678.0000 - fn: 25091.0000 - accuracy: 0.9363 - precision: 0.9648 - recall: 0.9060 - auc: 0.9826 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1605 - tp: 244637.0000 - fp: 8932.0000 - tn: 259692.0000 - fn: 25363.0000 - accuracy: 0.9363 - precision: 0.9648 - recall: 0.9061 - auc: 0.9826 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1604 - tp: 247431.0000 - fp: 9028.0000 - tn: 262662.0000 - fn: 25647.0000 - accuracy: 0.9363 - precision: 0.9648 - recall: 0.9061 - auc: 0.9827 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1603 - tp: 250298.0000 - fp: 9128.0000 - tn: 265570.0000 - fn: 25916.0000 - accuracy: 0.9364 - precision: 0.9648 - recall: 0.9062 - auc: 0.9827 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1602 - tp: 253087.0000 - fp: 9224.0000 - tn: 268549.0000 - fn: 26196.0000 - accuracy: 0.9364 - precision: 0.9648 - recall: 0.9062 - auc: 0.9827 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1601 - tp: 255932.0000 - fp: 9322.0000 - tn: 271459.0000 - fn: 26487.0000 - accuracy: 0.9364 - precision: 0.9649 - recall: 0.9062 - auc: 0.9827 - prc: 0.9855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1600 - tp: 258785.0000 - fp: 9416.0000 - tn: 274377.0000 - fn: 26766.0000 - accuracy: 0.9364 - precision: 0.9649 - recall: 0.9063 - auc: 0.9828 - prc: 0.9856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 21ms/step - loss: 0.1600 - tp: 258785.0000 - fp: 9416.0000 - tn: 274377.0000 - fn: 26766.0000 - accuracy: 0.9364 - precision: 0.9649 - recall: 0.9063 - auc: 0.9828 - prc: 0.9856 - val_loss: 0.0792 - val_tp: 59.0000 - val_fp: 589.0000 - val_tn: 44911.0000 - val_fn: 10.0000 - val_accuracy: 0.9869 - val_precision: 0.0910 - val_recall: 0.8551 - val_auc: 0.9628 - val_prc: 0.6624\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1491 - tp: 946.0000 - fp: 37.0000 - tn: 967.0000 - fn: 98.0000 - accuracy: 0.9341 - precision: 0.9624 - recall: 0.9061 - auc: 0.9860 - prc: 0.9882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1471 - tp: 4689.0000 - fp: 170.0000 - tn: 4935.0000 - fn: 446.0000 - accuracy: 0.9398 - precision: 0.9650 - recall: 0.9131 - auc: 0.9859 - prc: 0.9880"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.1508 - tp: 7436.0000 - fp: 278.0000 - tn: 7927.0000 - fn: 743.0000 - accuracy: 0.9377 - precision: 0.9640 - recall: 0.9092 - auc: 0.9853 - 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\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1498 - tp: 10233.0000 - fp: 369.0000 - tn: 10920.0000 - fn: 1006.0000 - accuracy: 0.9390 - precision: 0.9652 - recall: 0.9105 - auc: 0.9854 - 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",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1500 - tp: 12982.0000 - fp: 470.0000 - tn: 13943.0000 - fn: 1277.0000 - accuracy: 0.9391 - precision: 0.9651 - recall: 0.9104 - auc: 0.9855 - 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",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1485 - tp: 15741.0000 - fp: 564.0000 - tn: 16974.0000 - fn: 1537.0000 - accuracy: 0.9397 - precision: 0.9654 - recall: 0.9110 - auc: 0.9858 - 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\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1480 - tp: 18523.0000 - fp: 657.0000 - tn: 19978.0000 - fn: 1802.0000 - accuracy: 0.9400 - precision: 0.9657 - recall: 0.9113 - auc: 0.9859 - 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\r",
      " 22/278 [=>............................] - ETA: 5s - loss: 0.1482 - tp: 20374.0000 - fp: 718.0000 - tn: 21979.0000 - fn: 1985.0000 - accuracy: 0.9400 - precision: 0.9660 - recall: 0.9112 - auc: 0.9858 - 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\r",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1488 - tp: 23159.0000 - fp: 815.0000 - tn: 24972.0000 - fn: 2254.0000 - accuracy: 0.9401 - precision: 0.9660 - recall: 0.9113 - auc: 0.9857 - 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",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1481 - tp: 25966.0000 - fp: 880.0000 - tn: 27977.0000 - fn: 2521.0000 - accuracy: 0.9407 - precision: 0.9672 - recall: 0.9115 - auc: 0.9858 - 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\r",
      " 31/278 [==>...........................] - ETA: 5s - loss: 0.1480 - tp: 28669.0000 - fp: 984.0000 - tn: 31042.0000 - fn: 2793.0000 - accuracy: 0.9405 - precision: 0.9668 - recall: 0.9112 - auc: 0.9858 - 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\r",
      " 34/278 [==>...........................] - ETA: 5s - loss: 0.1485 - tp: 31463.0000 - fp: 1074.0000 - tn: 34029.0000 - fn: 3066.0000 - accuracy: 0.9405 - precision: 0.9670 - recall: 0.9112 - auc: 0.9857 - 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\r",
      " 37/278 [==>...........................] - ETA: 4s - loss: 0.1484 - tp: 34231.0000 - fp: 1179.0000 - tn: 37025.0000 - fn: 3341.0000 - accuracy: 0.9404 - precision: 0.9667 - recall: 0.9111 - auc: 0.9857 - 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\r",
      " 40/278 [===>..........................] - ETA: 4s - loss: 0.1483 - tp: 36998.0000 - fp: 1276.0000 - tn: 40050.0000 - fn: 3596.0000 - accuracy: 0.9405 - precision: 0.9667 - recall: 0.9114 - auc: 0.9857 - 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\r",
      " 43/278 [===>..........................] - ETA: 4s - loss: 0.1482 - tp: 39791.0000 - fp: 1383.0000 - tn: 43012.0000 - fn: 3878.0000 - accuracy: 0.9403 - precision: 0.9664 - recall: 0.9112 - auc: 0.9858 - 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\r",
      " 46/278 [===>..........................] - ETA: 4s - loss: 0.1478 - tp: 42555.0000 - fp: 1482.0000 - tn: 46022.0000 - fn: 4149.0000 - accuracy: 0.9402 - precision: 0.9663 - recall: 0.9112 - auc: 0.9859 - 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\r",
      " 49/278 [====>.........................] - ETA: 4s - loss: 0.1478 - tp: 45335.0000 - fp: 1559.0000 - tn: 49019.0000 - fn: 4439.0000 - accuracy: 0.9402 - precision: 0.9668 - recall: 0.9108 - auc: 0.9858 - 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\r",
      " 52/278 [====>.........................] - ETA: 4s - loss: 0.1478 - tp: 48106.0000 - fp: 1667.0000 - tn: 52030.0000 - fn: 4693.0000 - accuracy: 0.9403 - precision: 0.9665 - recall: 0.9111 - auc: 0.9858 - 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\r",
      " 55/278 [====>.........................] - ETA: 4s - loss: 0.1477 - tp: 50861.0000 - fp: 1762.0000 - tn: 55056.0000 - fn: 4961.0000 - accuracy: 0.9403 - precision: 0.9665 - recall: 0.9111 - auc: 0.9858 - 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\r",
      " 58/278 [=====>........................] - ETA: 4s - loss: 0.1473 - tp: 53688.0000 - fp: 1847.0000 - tn: 58019.0000 - fn: 5230.0000 - accuracy: 0.9404 - precision: 0.9667 - recall: 0.9112 - auc: 0.9859 - 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\r",
      " 61/278 [=====>........................] - ETA: 4s - loss: 0.1472 - tp: 56473.0000 - fp: 1945.0000 - tn: 61034.0000 - fn: 5476.0000 - accuracy: 0.9406 - precision: 0.9667 - recall: 0.9116 - auc: 0.9860 - 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\r",
      " 64/278 [=====>........................] - ETA: 4s - loss: 0.1472 - tp: 59272.0000 - fp: 2048.0000 - tn: 64003.0000 - fn: 5749.0000 - accuracy: 0.9405 - precision: 0.9666 - recall: 0.9116 - auc: 0.9860 - 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\r",
      " 67/278 [======>.......................] - ETA: 4s - loss: 0.1473 - tp: 61991.0000 - fp: 2137.0000 - tn: 67072.0000 - fn: 6016.0000 - accuracy: 0.9406 - precision: 0.9667 - recall: 0.9115 - auc: 0.9860 - 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\r",
      " 70/278 [======>.......................] - ETA: 4s - loss: 0.1472 - tp: 64776.0000 - fp: 2239.0000 - tn: 70062.0000 - fn: 6283.0000 - accuracy: 0.9406 - precision: 0.9666 - recall: 0.9116 - auc: 0.9860 - 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\r",
      " 73/278 [======>.......................] - ETA: 4s - loss: 0.1471 - tp: 67537.0000 - fp: 2338.0000 - tn: 73063.0000 - fn: 6566.0000 - accuracy: 0.9404 - precision: 0.9665 - recall: 0.9114 - auc: 0.9860 - 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\r",
      " 76/278 [=======>......................] - ETA: 4s - loss: 0.1475 - tp: 70320.0000 - fp: 2442.0000 - tn: 76035.0000 - fn: 6851.0000 - accuracy: 0.9403 - precision: 0.9664 - recall: 0.9112 - auc: 0.9860 - 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\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 0.1473 - tp: 73157.0000 - fp: 2541.0000 - tn: 78987.0000 - fn: 7107.0000 - accuracy: 0.9404 - precision: 0.9664 - recall: 0.9115 - auc: 0.9860 - 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\r",
      " 82/278 [=======>......................] - ETA: 4s - loss: 0.1471 - tp: 75990.0000 - fp: 2618.0000 - tn: 81957.0000 - fn: 7371.0000 - accuracy: 0.9405 - precision: 0.9667 - recall: 0.9116 - auc: 0.9860 - 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\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 0.1469 - tp: 78808.0000 - fp: 2696.0000 - tn: 84932.0000 - fn: 7644.0000 - accuracy: 0.9406 - precision: 0.9669 - recall: 0.9116 - auc: 0.9861 - 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\r",
      " 88/278 [========>.....................] - ETA: 3s - loss: 0.1467 - tp: 81574.0000 - fp: 2779.0000 - tn: 87956.0000 - fn: 7915.0000 - accuracy: 0.9407 - precision: 0.9671 - recall: 0.9116 - auc: 0.9861 - 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\r",
      " 91/278 [========>.....................] - ETA: 3s - loss: 0.1464 - tp: 84421.0000 - fp: 2855.0000 - tn: 90927.0000 - fn: 8165.0000 - accuracy: 0.9409 - precision: 0.9673 - recall: 0.9118 - auc: 0.9862 - 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\b\b\b\b\b\b\b\b\r",
      " 94/278 [=========>....................] - ETA: 3s - loss: 0.1463 - tp: 87268.0000 - fp: 2938.0000 - tn: 93867.0000 - fn: 8439.0000 - accuracy: 0.9409 - precision: 0.9674 - recall: 0.9118 - auc: 0.9862 - 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\b\b\b\b\b\b\b\b\r",
      " 97/278 [=========>....................] - ETA: 3s - loss: 0.1460 - tp: 90020.0000 - fp: 3005.0000 - tn: 96919.0000 - fn: 8712.0000 - accuracy: 0.9410 - precision: 0.9677 - recall: 0.9118 - auc: 0.9862 - 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\b\b\b\b\b\b\b\b\r",
      "100/278 [=========>....................] - ETA: 3s - loss: 0.1459 - tp: 92884.0000 - fp: 3098.0000 - tn: 99835.0000 - fn: 8983.0000 - accuracy: 0.9410 - precision: 0.9677 - recall: 0.9118 - auc: 0.9863 - prc: 0.9879"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1456 - tp: 95656.0000 - fp: 3177.0000 - tn: 102869.0000 - fn: 9242.0000 - accuracy: 0.9411 - precision: 0.9679 - recall: 0.9119 - auc: 0.9863 - prc: 0.9879"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1455 - tp: 98499.0000 - fp: 3271.0000 - tn: 105809.0000 - fn: 9509.0000 - accuracy: 0.9411 - precision: 0.9679 - recall: 0.9120 - auc: 0.9864 - prc: 0.9879"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1452 - tp: 101281.0000 - fp: 3362.0000 - tn: 108830.0000 - fn: 9759.0000 - accuracy: 0.9412 - precision: 0.9679 - recall: 0.9121 - auc: 0.9864 - prc: 0.9880"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1450 - tp: 104052.0000 - fp: 3448.0000 - tn: 111844.0000 - fn: 10032.0000 - accuracy: 0.9412 - precision: 0.9679 - recall: 0.9121 - auc: 0.9865 - prc: 0.9880"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1449 - tp: 106816.0000 - fp: 3535.0000 - tn: 114870.0000 - fn: 10299.0000 - accuracy: 0.9413 - precision: 0.9680 - recall: 0.9121 - auc: 0.9865 - prc: 0.9881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1448 - tp: 109641.0000 - fp: 3620.0000 - tn: 117847.0000 - fn: 10556.0000 - accuracy: 0.9413 - precision: 0.9680 - recall: 0.9122 - auc: 0.9865 - prc: 0.9881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1447 - tp: 111498.0000 - fp: 3681.0000 - tn: 119854.0000 - fn: 10727.0000 - accuracy: 0.9414 - precision: 0.9680 - recall: 0.9122 - auc: 0.9865 - prc: 0.9881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1446 - tp: 114347.0000 - fp: 3784.0000 - tn: 122778.0000 - fn: 10995.0000 - accuracy: 0.9413 - precision: 0.9680 - recall: 0.9123 - auc: 0.9866 - prc: 0.9881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1445 - tp: 117183.0000 - fp: 3874.0000 - tn: 125718.0000 - fn: 11273.0000 - accuracy: 0.9413 - precision: 0.9680 - recall: 0.9122 - auc: 0.9866 - prc: 0.9881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1444 - tp: 120015.0000 - fp: 3982.0000 - tn: 128668.0000 - fn: 11527.0000 - accuracy: 0.9413 - precision: 0.9679 - recall: 0.9124 - auc: 0.9866 - prc: 0.9882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1442 - tp: 122806.0000 - fp: 4076.0000 - tn: 131671.0000 - fn: 11783.0000 - accuracy: 0.9413 - precision: 0.9679 - recall: 0.9125 - auc: 0.9867 - prc: 0.9882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1441 - tp: 125606.0000 - fp: 4176.0000 - tn: 134662.0000 - fn: 12036.0000 - accuracy: 0.9414 - precision: 0.9678 - recall: 0.9126 - auc: 0.9867 - prc: 0.9882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1440 - tp: 128450.0000 - fp: 4252.0000 - tn: 137618.0000 - fn: 12304.0000 - accuracy: 0.9414 - precision: 0.9680 - recall: 0.9126 - auc: 0.9867 - prc: 0.9882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1438 - tp: 131226.0000 - fp: 4334.0000 - tn: 140666.0000 - fn: 12542.0000 - accuracy: 0.9416 - precision: 0.9680 - recall: 0.9128 - auc: 0.9868 - prc: 0.9883"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1437 - tp: 134032.0000 - fp: 4410.0000 - tn: 143683.0000 - fn: 12787.0000 - accuracy: 0.9417 - precision: 0.9681 - recall: 0.9129 - auc: 0.9868 - prc: 0.9883"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1436 - tp: 136846.0000 - fp: 4506.0000 - tn: 146655.0000 - fn: 13049.0000 - accuracy: 0.9417 - precision: 0.9681 - recall: 0.9129 - auc: 0.9868 - prc: 0.9883"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1435 - tp: 139664.0000 - fp: 4588.0000 - tn: 149631.0000 - fn: 13317.0000 - accuracy: 0.9417 - precision: 0.9682 - recall: 0.9129 - auc: 0.9868 - prc: 0.9883"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "153/278 [===============>..............] - ETA: 2s - loss: 0.1434 - tp: 142486.0000 - fp: 4682.0000 - tn: 152603.0000 - fn: 13573.0000 - accuracy: 0.9417 - precision: 0.9682 - recall: 0.9130 - auc: 0.9869 - prc: 0.9883"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1432 - tp: 145279.0000 - fp: 4773.0000 - tn: 155614.0000 - fn: 13822.0000 - accuracy: 0.9418 - precision: 0.9682 - recall: 0.9131 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1433 - tp: 148053.0000 - fp: 4866.0000 - tn: 158626.0000 - fn: 14087.0000 - accuracy: 0.9418 - precision: 0.9682 - recall: 0.9131 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1432 - tp: 150833.0000 - fp: 4979.0000 - tn: 161630.0000 - fn: 14334.0000 - accuracy: 0.9418 - precision: 0.9680 - recall: 0.9132 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1433 - tp: 153646.0000 - fp: 5066.0000 - tn: 164608.0000 - fn: 14600.0000 - accuracy: 0.9418 - precision: 0.9681 - recall: 0.9132 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1431 - tp: 156458.0000 - fp: 5152.0000 - tn: 167593.0000 - fn: 14861.0000 - accuracy: 0.9418 - precision: 0.9681 - recall: 0.9133 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1431 - tp: 159267.0000 - fp: 5243.0000 - tn: 170583.0000 - fn: 15115.0000 - accuracy: 0.9419 - precision: 0.9681 - recall: 0.9133 - auc: 0.9869 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1430 - tp: 162130.0000 - fp: 5335.0000 - tn: 173502.0000 - fn: 15385.0000 - accuracy: 0.9419 - precision: 0.9681 - recall: 0.9133 - auc: 0.9870 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1428 - tp: 164918.0000 - fp: 5421.0000 - tn: 176520.0000 - fn: 15637.0000 - accuracy: 0.9419 - precision: 0.9682 - recall: 0.9134 - auc: 0.9870 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1428 - tp: 167729.0000 - fp: 5519.0000 - tn: 179499.0000 - fn: 15893.0000 - accuracy: 0.9419 - precision: 0.9681 - recall: 0.9134 - auc: 0.9870 - prc: 0.9884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1427 - tp: 170585.0000 - fp: 5599.0000 - tn: 182419.0000 - fn: 16181.0000 - accuracy: 0.9419 - precision: 0.9682 - recall: 0.9134 - auc: 0.9870 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1427 - tp: 173395.0000 - fp: 5681.0000 - tn: 185409.0000 - fn: 16443.0000 - accuracy: 0.9419 - precision: 0.9683 - recall: 0.9134 - auc: 0.9870 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1426 - tp: 176199.0000 - fp: 5764.0000 - tn: 188405.0000 - fn: 16704.0000 - accuracy: 0.9420 - precision: 0.9683 - recall: 0.9134 - auc: 0.9870 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1426 - tp: 178951.0000 - fp: 5878.0000 - tn: 191436.0000 - fn: 16951.0000 - accuracy: 0.9419 - precision: 0.9682 - recall: 0.9135 - auc: 0.9870 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1424 - tp: 181838.0000 - fp: 5955.0000 - tn: 194375.0000 - fn: 17192.0000 - accuracy: 0.9420 - precision: 0.9683 - recall: 0.9136 - auc: 0.9871 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1423 - tp: 184634.0000 - fp: 6032.0000 - tn: 197384.0000 - fn: 17454.0000 - accuracy: 0.9421 - precision: 0.9684 - recall: 0.9136 - auc: 0.9871 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1422 - tp: 187405.0000 - fp: 6114.0000 - tn: 200421.0000 - fn: 17708.0000 - accuracy: 0.9421 - precision: 0.9684 - recall: 0.9137 - auc: 0.9871 - prc: 0.9885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1422 - tp: 190191.0000 - fp: 6206.0000 - tn: 203449.0000 - fn: 17946.0000 - accuracy: 0.9422 - precision: 0.9684 - recall: 0.9138 - auc: 0.9871 - prc: 0.9886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1420 - tp: 192958.0000 - fp: 6289.0000 - tn: 206478.0000 - fn: 18211.0000 - accuracy: 0.9422 - precision: 0.9684 - recall: 0.9138 - auc: 0.9872 - prc: 0.9886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1419 - tp: 195719.0000 - fp: 6373.0000 - tn: 209525.0000 - fn: 18463.0000 - accuracy: 0.9423 - precision: 0.9685 - recall: 0.9138 - auc: 0.9872 - prc: 0.9886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1418 - tp: 198524.0000 - fp: 6452.0000 - tn: 212536.0000 - fn: 18712.0000 - accuracy: 0.9423 - precision: 0.9685 - recall: 0.9139 - auc: 0.9872 - prc: 0.9886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1417 - tp: 201343.0000 - fp: 6537.0000 - tn: 215524.0000 - fn: 18964.0000 - accuracy: 0.9424 - precision: 0.9686 - recall: 0.9139 - auc: 0.9873 - prc: 0.9886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1416 - tp: 204191.0000 - fp: 6626.0000 - tn: 218465.0000 - fn: 19230.0000 - accuracy: 0.9424 - precision: 0.9686 - recall: 0.9139 - auc: 0.9873 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1415 - tp: 207053.0000 - fp: 6715.0000 - tn: 221404.0000 - fn: 19484.0000 - accuracy: 0.9424 - precision: 0.9686 - recall: 0.9140 - auc: 0.9873 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1414 - tp: 209928.0000 - fp: 6796.0000 - tn: 224350.0000 - fn: 19726.0000 - accuracy: 0.9424 - precision: 0.9686 - recall: 0.9141 - auc: 0.9873 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1413 - tp: 212755.0000 - fp: 6873.0000 - tn: 227346.0000 - fn: 19970.0000 - accuracy: 0.9425 - precision: 0.9687 - recall: 0.9142 - auc: 0.9873 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.1412 - tp: 215639.0000 - fp: 6955.0000 - tn: 230250.0000 - fn: 20244.0000 - accuracy: 0.9425 - precision: 0.9688 - recall: 0.9142 - auc: 0.9874 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1412 - tp: 218468.0000 - fp: 7041.0000 - tn: 233219.0000 - fn: 20504.0000 - accuracy: 0.9425 - precision: 0.9688 - recall: 0.9142 - auc: 0.9874 - prc: 0.9887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1411 - tp: 221305.0000 - fp: 7117.0000 - tn: 236196.0000 - fn: 20758.0000 - accuracy: 0.9426 - precision: 0.9688 - recall: 0.9142 - auc: 0.9874 - prc: 0.9888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1410 - tp: 224077.0000 - fp: 7207.0000 - tn: 239231.0000 - fn: 21005.0000 - accuracy: 0.9426 - precision: 0.9688 - recall: 0.9143 - auc: 0.9874 - prc: 0.9888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1409 - tp: 226901.0000 - fp: 7300.0000 - tn: 242209.0000 - fn: 21254.0000 - accuracy: 0.9426 - precision: 0.9688 - recall: 0.9144 - auc: 0.9874 - prc: 0.9888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1407 - tp: 229714.0000 - fp: 7376.0000 - tn: 245226.0000 - fn: 21492.0000 - accuracy: 0.9427 - precision: 0.9689 - recall: 0.9144 - auc: 0.9875 - prc: 0.9888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1406 - tp: 232534.0000 - fp: 7455.0000 - tn: 248235.0000 - fn: 21728.0000 - accuracy: 0.9428 - precision: 0.9689 - recall: 0.9145 - auc: 0.9875 - 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\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1404 - tp: 235310.0000 - fp: 7540.0000 - tn: 251270.0000 - fn: 21976.0000 - accuracy: 0.9428 - precision: 0.9690 - recall: 0.9146 - auc: 0.9875 - 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\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1404 - tp: 238079.0000 - fp: 7635.0000 - tn: 254288.0000 - fn: 22238.0000 - accuracy: 0.9428 - precision: 0.9689 - recall: 0.9146 - auc: 0.9875 - 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\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1403 - tp: 240830.0000 - fp: 7719.0000 - tn: 257352.0000 - fn: 22483.0000 - accuracy: 0.9428 - precision: 0.9689 - recall: 0.9146 - auc: 0.9876 - 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\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1401 - tp: 243651.0000 - fp: 7800.0000 - tn: 260338.0000 - fn: 22739.0000 - accuracy: 0.9429 - precision: 0.9690 - recall: 0.9146 - auc: 0.9876 - 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\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1400 - tp: 246511.0000 - fp: 7882.0000 - tn: 263287.0000 - fn: 22992.0000 - accuracy: 0.9429 - precision: 0.9690 - recall: 0.9147 - auc: 0.9876 - 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\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1400 - tp: 249321.0000 - fp: 7957.0000 - tn: 266308.0000 - fn: 23230.0000 - accuracy: 0.9430 - precision: 0.9691 - recall: 0.9148 - auc: 0.9876 - 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\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1399 - tp: 252233.0000 - fp: 8038.0000 - tn: 269213.0000 - fn: 23476.0000 - accuracy: 0.9430 - precision: 0.9691 - recall: 0.9149 - auc: 0.9877 - 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\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1398 - tp: 255047.0000 - fp: 8115.0000 - tn: 272211.0000 - fn: 23731.0000 - accuracy: 0.9430 - precision: 0.9692 - recall: 0.9149 - auc: 0.9877 - 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\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1397 - tp: 257797.0000 - fp: 8200.0000 - tn: 275263.0000 - fn: 23988.0000 - accuracy: 0.9431 - precision: 0.9692 - recall: 0.9149 - auc: 0.9877 - 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\b\r",
      "278/278 [==============================] - 6s 21ms/step - loss: 0.1396 - tp: 259655.0000 - fp: 8254.0000 - tn: 277278.0000 - fn: 24157.0000 - accuracy: 0.9431 - precision: 0.9692 - recall: 0.9149 - auc: 0.9877 - prc: 0.9890 - val_loss: 0.0699 - val_tp: 60.0000 - val_fp: 585.0000 - val_tn: 44915.0000 - val_fn: 9.0000 - val_accuracy: 0.9870 - val_precision: 0.0930 - val_recall: 0.8696 - val_auc: 0.9584 - val_prc: 0.6478\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1263 - tp: 956.0000 - fp: 16.0000 - tn: 988.0000 - fn: 88.0000 - accuracy: 0.9492 - precision: 0.9835 - recall: 0.9157 - auc: 0.9907 - 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\r",
      "  4/278 [..............................] - ETA: 4s - loss: 0.1257 - tp: 3724.0000 - fp: 98.0000 - tn: 4038.0000 - fn: 332.0000 - accuracy: 0.9475 - precision: 0.9744 - recall: 0.9181 - auc: 0.9905 - 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\r",
      "  7/278 [..............................] - ETA: 5s - loss: 0.1316 - tp: 6543.0000 - fp: 189.0000 - tn: 7009.0000 - fn: 595.0000 - accuracy: 0.9453 - precision: 0.9719 - recall: 0.9166 - auc: 0.9894 - 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\r",
      " 10/278 [>.............................] - ETA: 5s - loss: 0.1324 - tp: 9369.0000 - fp: 261.0000 - tn: 9985.0000 - fn: 865.0000 - accuracy: 0.9450 - precision: 0.9729 - recall: 0.9155 - auc: 0.9893 - prc: 0.9902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1321 - tp: 12166.0000 - fp: 337.0000 - tn: 12990.0000 - fn: 1131.0000 - accuracy: 0.9449 - precision: 0.9730 - recall: 0.9149 - auc: 0.9894 - 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\b\r",
      " 16/278 [>.............................] - ETA: 5s - loss: 0.1303 - tp: 15057.0000 - fp: 406.0000 - tn: 15926.0000 - fn: 1379.0000 - accuracy: 0.9455 - precision: 0.9737 - recall: 0.9161 - auc: 0.9897 - 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\r",
      " 19/278 [=>............................] - ETA: 5s - loss: 0.1302 - tp: 17840.0000 - fp: 493.0000 - tn: 18963.0000 - fn: 1616.0000 - accuracy: 0.9458 - precision: 0.9731 - recall: 0.9169 - auc: 0.9897 - 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",
      " 22/278 [=>............................] - ETA: 5s - loss: 0.1303 - tp: 20621.0000 - fp: 579.0000 - tn: 21977.0000 - fn: 1879.0000 - accuracy: 0.9454 - precision: 0.9727 - recall: 0.9165 - auc: 0.9897 - 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",
      " 25/278 [=>............................] - ETA: 5s - loss: 0.1298 - tp: 23358.0000 - fp: 671.0000 - tn: 25063.0000 - fn: 2108.0000 - accuracy: 0.9457 - precision: 0.9721 - recall: 0.9172 - auc: 0.9897 - 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",
      " 28/278 [==>...........................] - ETA: 5s - loss: 0.1302 - tp: 26199.0000 - fp: 772.0000 - tn: 28027.0000 - fn: 2346.0000 - accuracy: 0.9456 - precision: 0.9714 - recall: 0.9178 - auc: 0.9896 - 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",
      " 31/278 [==>...........................] - ETA: 5s - loss: 0.1303 - tp: 29049.0000 - fp: 853.0000 - tn: 30985.0000 - fn: 2601.0000 - accuracy: 0.9456 - precision: 0.9715 - recall: 0.9178 - auc: 0.9896 - 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",
      " 34/278 [==>...........................] - ETA: 4s - loss: 0.1305 - tp: 31868.0000 - fp: 947.0000 - tn: 33959.0000 - fn: 2858.0000 - accuracy: 0.9454 - precision: 0.9711 - recall: 0.9177 - auc: 0.9896 - 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",
      " 37/278 [==>...........................] - ETA: 4s - loss: 0.1303 - tp: 34741.0000 - fp: 1024.0000 - tn: 36914.0000 - fn: 3097.0000 - accuracy: 0.9456 - precision: 0.9714 - recall: 0.9182 - auc: 0.9896 - 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",
      " 40/278 [===>..........................] - ETA: 4s - loss: 0.1303 - tp: 37471.0000 - fp: 1119.0000 - tn: 39976.0000 - fn: 3354.0000 - accuracy: 0.9454 - precision: 0.9710 - recall: 0.9178 - auc: 0.9896 - 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",
      " 43/278 [===>..........................] - ETA: 4s - loss: 0.1305 - tp: 40242.0000 - fp: 1208.0000 - tn: 43000.0000 - fn: 3614.0000 - accuracy: 0.9452 - precision: 0.9709 - recall: 0.9176 - auc: 0.9896 - prc: 0.9904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1304 - tp: 42995.0000 - fp: 1296.0000 - tn: 46071.0000 - fn: 3846.0000 - accuracy: 0.9454 - precision: 0.9707 - recall: 0.9179 - auc: 0.9896 - prc: 0.9904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1304 - tp: 45838.0000 - fp: 1376.0000 - tn: 49066.0000 - fn: 4072.0000 - accuracy: 0.9457 - precision: 0.9709 - recall: 0.9184 - auc: 0.9896 - prc: 0.9904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1304 - tp: 48631.0000 - fp: 1465.0000 - tn: 52070.0000 - fn: 4330.0000 - accuracy: 0.9456 - precision: 0.9708 - recall: 0.9182 - auc: 0.9896 - prc: 0.9904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1303 - tp: 51443.0000 - fp: 1543.0000 - tn: 55078.0000 - fn: 4576.0000 - accuracy: 0.9457 - precision: 0.9709 - recall: 0.9183 - auc: 0.9896 - 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",
      " 58/278 [=====>........................] - ETA: 4s - loss: 0.1301 - tp: 54244.0000 - fp: 1624.0000 - tn: 58093.0000 - fn: 4823.0000 - accuracy: 0.9457 - precision: 0.9709 - recall: 0.9183 - auc: 0.9897 - 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",
      " 61/278 [=====>........................] - ETA: 4s - loss: 0.1301 - tp: 57069.0000 - fp: 1726.0000 - tn: 61071.0000 - fn: 5062.0000 - accuracy: 0.9457 - precision: 0.9706 - recall: 0.9185 - auc: 0.9897 - 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",
      " 64/278 [=====>........................] - ETA: 4s - loss: 0.1301 - tp: 59929.0000 - fp: 1813.0000 - tn: 64017.0000 - fn: 5313.0000 - accuracy: 0.9456 - precision: 0.9706 - recall: 0.9186 - auc: 0.9897 - 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",
      " 66/278 [======>.......................] - ETA: 4s - loss: 0.1302 - tp: 61783.0000 - fp: 1869.0000 - tn: 66034.0000 - fn: 5482.0000 - accuracy: 0.9456 - precision: 0.9706 - recall: 0.9185 - auc: 0.9897 - 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",
      " 69/278 [======>.......................] - ETA: 4s - loss: 0.1301 - tp: 64587.0000 - fp: 1954.0000 - tn: 69034.0000 - fn: 5737.0000 - accuracy: 0.9456 - precision: 0.9706 - recall: 0.9184 - auc: 0.9897 - 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",
      " 72/278 [======>.......................] - ETA: 4s - loss: 0.1301 - tp: 67396.0000 - fp: 2031.0000 - tn: 72054.0000 - fn: 5975.0000 - accuracy: 0.9457 - precision: 0.9707 - recall: 0.9186 - auc: 0.9897 - 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",
      " 75/278 [=======>......................] - ETA: 4s - loss: 0.1300 - tp: 70273.0000 - fp: 2112.0000 - tn: 75029.0000 - fn: 6186.0000 - accuracy: 0.9460 - precision: 0.9708 - recall: 0.9191 - auc: 0.9897 - 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",
      " 78/278 [=======>......................] - ETA: 4s - loss: 0.1300 - tp: 73105.0000 - fp: 2202.0000 - tn: 78002.0000 - fn: 6435.0000 - accuracy: 0.9459 - precision: 0.9708 - recall: 0.9191 - auc: 0.9897 - 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",
      " 81/278 [=======>......................] - ETA: 4s - loss: 0.1298 - tp: 75896.0000 - fp: 2298.0000 - tn: 81027.0000 - fn: 6667.0000 - accuracy: 0.9460 - precision: 0.9706 - recall: 0.9192 - auc: 0.9898 - 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",
      " 84/278 [========>.....................] - ETA: 3s - loss: 0.1296 - tp: 78775.0000 - fp: 2391.0000 - tn: 83956.0000 - fn: 6910.0000 - accuracy: 0.9459 - precision: 0.9705 - recall: 0.9194 - auc: 0.9898 - 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",
      " 87/278 [========>.....................] - ETA: 3s - loss: 0.1295 - tp: 81627.0000 - fp: 2471.0000 - tn: 86933.0000 - fn: 7145.0000 - accuracy: 0.9460 - precision: 0.9706 - recall: 0.9195 - auc: 0.9898 - 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",
      " 90/278 [========>.....................] - ETA: 3s - loss: 0.1295 - tp: 84430.0000 - fp: 2557.0000 - tn: 89937.0000 - fn: 7396.0000 - accuracy: 0.9460 - precision: 0.9706 - recall: 0.9195 - auc: 0.9899 - 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",
      " 93/278 [=========>....................] - ETA: 3s - loss: 0.1295 - tp: 87181.0000 - fp: 2643.0000 - tn: 92999.0000 - fn: 7641.0000 - accuracy: 0.9460 - precision: 0.9706 - recall: 0.9194 - auc: 0.9898 - 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",
      " 95/278 [=========>....................] - ETA: 3s - loss: 0.1294 - tp: 89059.0000 - fp: 2709.0000 - tn: 94989.0000 - fn: 7803.0000 - accuracy: 0.9460 - precision: 0.9705 - recall: 0.9194 - auc: 0.9899 - 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",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.1293 - tp: 91920.0000 - fp: 2785.0000 - tn: 97956.0000 - fn: 8043.0000 - accuracy: 0.9460 - precision: 0.9706 - recall: 0.9195 - auc: 0.9899 - 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",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1291 - tp: 94833.0000 - fp: 2870.0000 - tn: 100869.0000 - fn: 8276.0000 - accuracy: 0.9461 - precision: 0.9706 - recall: 0.9197 - auc: 0.9899 - 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\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1289 - tp: 97683.0000 - fp: 2942.0000 - tn: 103841.0000 - fn: 8526.0000 - accuracy: 0.9462 - precision: 0.9708 - recall: 0.9197 - auc: 0.9899 - 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\r",
      "107/278 [==========>...................] - ETA: 3s - loss: 0.1288 - tp: 100532.0000 - fp: 3026.0000 - tn: 106802.0000 - fn: 8776.0000 - accuracy: 0.9461 - precision: 0.9708 - recall: 0.9197 - auc: 0.9899 - 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",
      "110/278 [==========>...................] - ETA: 3s - loss: 0.1287 - tp: 103341.0000 - fp: 3094.0000 - tn: 109825.0000 - fn: 9020.0000 - accuracy: 0.9462 - precision: 0.9709 - recall: 0.9197 - auc: 0.9900 - 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",
      "113/278 [===========>..................] - ETA: 3s - loss: 0.1285 - tp: 106110.0000 - fp: 3162.0000 - tn: 112925.0000 - fn: 9227.0000 - accuracy: 0.9465 - precision: 0.9711 - recall: 0.9200 - auc: 0.9900 - 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",
      "116/278 [===========>..................] - ETA: 3s - loss: 0.1287 - tp: 108993.0000 - fp: 3244.0000 - tn: 115846.0000 - fn: 9485.0000 - accuracy: 0.9464 - precision: 0.9711 - recall: 0.9199 - auc: 0.9900 - 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",
      "119/278 [===========>..................] - ETA: 3s - loss: 0.1287 - tp: 111886.0000 - fp: 3324.0000 - tn: 118766.0000 - fn: 9736.0000 - accuracy: 0.9464 - precision: 0.9711 - recall: 0.9199 - auc: 0.9900 - 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",
      "122/278 [============>.................] - ETA: 3s - loss: 0.1285 - tp: 114704.0000 - fp: 3402.0000 - tn: 121781.0000 - fn: 9969.0000 - accuracy: 0.9465 - precision: 0.9712 - recall: 0.9200 - auc: 0.9900 - 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",
      "125/278 [============>.................] - ETA: 3s - loss: 0.1284 - tp: 117504.0000 - fp: 3487.0000 - tn: 124795.0000 - fn: 10214.0000 - accuracy: 0.9465 - precision: 0.9712 - recall: 0.9200 - auc: 0.9900 - 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",
      "128/278 [============>.................] - ETA: 3s - loss: 0.1285 - tp: 120347.0000 - fp: 3582.0000 - tn: 127745.0000 - fn: 10470.0000 - accuracy: 0.9464 - precision: 0.9711 - recall: 0.9200 - auc: 0.9900 - 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",
      "131/278 [=============>................] - ETA: 3s - loss: 0.1283 - tp: 123117.0000 - fp: 3665.0000 - tn: 130819.0000 - fn: 10687.0000 - accuracy: 0.9465 - precision: 0.9711 - recall: 0.9201 - auc: 0.9900 - 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",
      "134/278 [=============>................] - ETA: 2s - loss: 0.1282 - tp: 125964.0000 - fp: 3748.0000 - tn: 133797.0000 - fn: 10923.0000 - accuracy: 0.9465 - precision: 0.9711 - recall: 0.9202 - auc: 0.9901 - 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",
      "137/278 [=============>................] - ETA: 2s - loss: 0.1281 - tp: 128799.0000 - fp: 3825.0000 - tn: 136780.0000 - fn: 11172.0000 - accuracy: 0.9465 - precision: 0.9712 - recall: 0.9202 - auc: 0.9901 - 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",
      "140/278 [==============>...............] - ETA: 2s - loss: 0.1283 - tp: 131613.0000 - fp: 3910.0000 - tn: 139771.0000 - fn: 11426.0000 - accuracy: 0.9465 - precision: 0.9711 - recall: 0.9201 - auc: 0.9901 - 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",
      "143/278 [==============>...............] - ETA: 2s - loss: 0.1281 - tp: 134418.0000 - fp: 3999.0000 - tn: 142796.0000 - fn: 11651.0000 - accuracy: 0.9466 - precision: 0.9711 - recall: 0.9202 - auc: 0.9901 - 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",
      "146/278 [==============>...............] - ETA: 2s - loss: 0.1282 - tp: 137253.0000 - fp: 4069.0000 - tn: 145786.0000 - fn: 11900.0000 - accuracy: 0.9466 - precision: 0.9712 - recall: 0.9202 - auc: 0.9901 - 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",
      "149/278 [===============>..............] - ETA: 2s - loss: 0.1282 - tp: 140066.0000 - fp: 4165.0000 - tn: 148787.0000 - fn: 12134.0000 - accuracy: 0.9466 - precision: 0.9711 - recall: 0.9203 - auc: 0.9901 - 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",
      "152/278 [===============>..............] - ETA: 2s - loss: 0.1280 - tp: 142949.0000 - fp: 4240.0000 - tn: 151755.0000 - fn: 12352.0000 - accuracy: 0.9467 - precision: 0.9712 - recall: 0.9205 - auc: 0.9901 - 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",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1281 - tp: 145776.0000 - fp: 4345.0000 - tn: 154718.0000 - fn: 12601.0000 - accuracy: 0.9466 - precision: 0.9711 - recall: 0.9204 - auc: 0.9901 - 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",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1281 - tp: 148592.0000 - fp: 4425.0000 - tn: 157716.0000 - fn: 12851.0000 - accuracy: 0.9466 - precision: 0.9711 - recall: 0.9204 - auc: 0.9901 - 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",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1280 - tp: 151476.0000 - fp: 4490.0000 - tn: 160667.0000 - fn: 13095.0000 - accuracy: 0.9467 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1281 - tp: 154302.0000 - fp: 4578.0000 - tn: 163646.0000 - fn: 13346.0000 - accuracy: 0.9466 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1279 - tp: 157088.0000 - fp: 4649.0000 - tn: 166693.0000 - fn: 13586.0000 - accuracy: 0.9467 - precision: 0.9713 - recall: 0.9204 - auc: 0.9901 - 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",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1278 - tp: 159917.0000 - fp: 4736.0000 - tn: 169684.0000 - fn: 13823.0000 - accuracy: 0.9467 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1279 - tp: 162726.0000 - fp: 4822.0000 - tn: 172698.0000 - fn: 14058.0000 - accuracy: 0.9467 - precision: 0.9712 - recall: 0.9205 - auc: 0.9901 - 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",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1278 - tp: 165538.0000 - fp: 4910.0000 - tn: 175694.0000 - fn: 14306.0000 - accuracy: 0.9467 - precision: 0.9712 - recall: 0.9205 - auc: 0.9901 - 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",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1278 - tp: 168410.0000 - fp: 4991.0000 - tn: 178619.0000 - fn: 14572.0000 - accuracy: 0.9466 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "182/278 [==================>...........] - ETA: 1s - loss: 0.1277 - tp: 171238.0000 - fp: 5078.0000 - tn: 181602.0000 - fn: 14818.0000 - accuracy: 0.9466 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "185/278 [==================>...........] - ETA: 1s - loss: 0.1277 - tp: 174096.0000 - fp: 5154.0000 - tn: 184570.0000 - fn: 15060.0000 - accuracy: 0.9466 - precision: 0.9712 - recall: 0.9204 - auc: 0.9901 - 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",
      "188/278 [===================>..........] - ETA: 1s - loss: 0.1276 - tp: 176881.0000 - fp: 5233.0000 - tn: 187604.0000 - fn: 15306.0000 - accuracy: 0.9467 - precision: 0.9713 - recall: 0.9204 - auc: 0.9902 - 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",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1275 - tp: 179705.0000 - fp: 5308.0000 - tn: 190598.0000 - fn: 15557.0000 - accuracy: 0.9467 - precision: 0.9713 - recall: 0.9203 - auc: 0.9902 - 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",
      "194/278 [===================>..........] - ETA: 1s - loss: 0.1275 - tp: 182486.0000 - fp: 5372.0000 - tn: 193648.0000 - fn: 15806.0000 - accuracy: 0.9467 - precision: 0.9714 - recall: 0.9203 - auc: 0.9902 - 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",
      "197/278 [====================>.........] - ETA: 1s - loss: 0.1275 - tp: 185331.0000 - fp: 5465.0000 - tn: 196594.0000 - fn: 16066.0000 - accuracy: 0.9466 - precision: 0.9714 - recall: 0.9202 - auc: 0.9902 - 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",
      "200/278 [====================>.........] - ETA: 1s - loss: 0.1274 - tp: 188140.0000 - fp: 5547.0000 - tn: 199609.0000 - fn: 16304.0000 - accuracy: 0.9467 - precision: 0.9714 - recall: 0.9203 - auc: 0.9902 - 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",
      "203/278 [====================>.........] - ETA: 1s - loss: 0.1273 - tp: 190989.0000 - fp: 5633.0000 - tn: 202576.0000 - fn: 16546.0000 - accuracy: 0.9467 - precision: 0.9714 - recall: 0.9203 - auc: 0.9902 - 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",
      "206/278 [=====================>........] - ETA: 1s - loss: 0.1273 - tp: 193821.0000 - fp: 5717.0000 - tn: 205566.0000 - fn: 16784.0000 - accuracy: 0.9467 - precision: 0.9713 - recall: 0.9203 - auc: 0.9902 - 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",
      "209/278 [=====================>........] - ETA: 1s - loss: 0.1272 - tp: 196619.0000 - fp: 5799.0000 - tn: 208617.0000 - fn: 16997.0000 - accuracy: 0.9467 - precision: 0.9714 - recall: 0.9204 - auc: 0.9902 - 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",
      "212/278 [=====================>........] - ETA: 1s - loss: 0.1272 - tp: 199402.0000 - fp: 5881.0000 - tn: 211648.0000 - fn: 17245.0000 - accuracy: 0.9467 - precision: 0.9714 - recall: 0.9204 - auc: 0.9902 - 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",
      "215/278 [======================>.......] - ETA: 1s - loss: 0.1271 - tp: 202191.0000 - fp: 5956.0000 - tn: 214702.0000 - fn: 17471.0000 - accuracy: 0.9468 - precision: 0.9714 - recall: 0.9205 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1270 - tp: 205050.0000 - fp: 6045.0000 - tn: 217666.0000 - fn: 17703.0000 - accuracy: 0.9468 - precision: 0.9714 - recall: 0.9205 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1269 - tp: 207894.0000 - fp: 6128.0000 - tn: 220652.0000 - fn: 17934.0000 - accuracy: 0.9468 - precision: 0.9714 - recall: 0.9206 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1269 - tp: 210671.0000 - fp: 6203.0000 - tn: 223694.0000 - fn: 18184.0000 - accuracy: 0.9468 - precision: 0.9714 - recall: 0.9205 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1268 - tp: 213538.0000 - fp: 6276.0000 - tn: 226648.0000 - fn: 18434.0000 - accuracy: 0.9468 - precision: 0.9714 - recall: 0.9205 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1268 - tp: 216406.0000 - fp: 6354.0000 - tn: 229607.0000 - fn: 18673.0000 - accuracy: 0.9469 - precision: 0.9715 - recall: 0.9206 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.1267 - tp: 219249.0000 - fp: 6437.0000 - tn: 232605.0000 - fn: 18893.0000 - accuracy: 0.9469 - precision: 0.9715 - recall: 0.9207 - auc: 0.9903 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1267 - tp: 222095.0000 - fp: 6522.0000 - tn: 235586.0000 - fn: 19125.0000 - accuracy: 0.9469 - precision: 0.9715 - recall: 0.9207 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1265 - tp: 224913.0000 - fp: 6599.0000 - tn: 238629.0000 - fn: 19331.0000 - accuracy: 0.9470 - precision: 0.9715 - recall: 0.9209 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1265 - tp: 227779.0000 - fp: 6682.0000 - tn: 241591.0000 - fn: 19564.0000 - accuracy: 0.9470 - precision: 0.9715 - recall: 0.9209 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 230625.0000 - fp: 6761.0000 - tn: 244574.0000 - fn: 19800.0000 - accuracy: 0.9471 - precision: 0.9715 - recall: 0.9209 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 233515.0000 - fp: 6835.0000 - tn: 247530.0000 - fn: 20024.0000 - accuracy: 0.9471 - precision: 0.9716 - recall: 0.9210 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 236300.0000 - fp: 6916.0000 - tn: 250560.0000 - fn: 20272.0000 - accuracy: 0.9471 - precision: 0.9716 - recall: 0.9210 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 239151.0000 - fp: 6995.0000 - tn: 253546.0000 - fn: 20500.0000 - accuracy: 0.9471 - precision: 0.9716 - recall: 0.9210 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 241942.0000 - fp: 7081.0000 - tn: 256575.0000 - fn: 20738.0000 - accuracy: 0.9471 - precision: 0.9716 - recall: 0.9211 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1264 - tp: 244801.0000 - fp: 7170.0000 - tn: 259530.0000 - fn: 20979.0000 - accuracy: 0.9471 - precision: 0.9715 - recall: 0.9211 - auc: 0.9904 - prc: 0.9910"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1263 - tp: 247677.0000 - fp: 7249.0000 - tn: 262499.0000 - fn: 21199.0000 - accuracy: 0.9472 - precision: 0.9716 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1263 - tp: 250535.0000 - fp: 7321.0000 - tn: 265451.0000 - fn: 21461.0000 - accuracy: 0.9472 - precision: 0.9716 - recall: 0.9211 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1262 - tp: 253387.0000 - fp: 7400.0000 - tn: 268438.0000 - fn: 21687.0000 - accuracy: 0.9472 - precision: 0.9716 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1261 - tp: 256242.0000 - fp: 7488.0000 - tn: 271403.0000 - fn: 21923.0000 - accuracy: 0.9472 - precision: 0.9716 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1262 - tp: 259032.0000 - fp: 7596.0000 - tn: 274409.0000 - fn: 22163.0000 - accuracy: 0.9472 - precision: 0.9715 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1261 - tp: 261849.0000 - fp: 7675.0000 - tn: 277421.0000 - fn: 22399.0000 - accuracy: 0.9472 - precision: 0.9715 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 21ms/step - loss: 0.1261 - tp: 261849.0000 - fp: 7675.0000 - tn: 277421.0000 - fn: 22399.0000 - accuracy: 0.9472 - precision: 0.9715 - recall: 0.9212 - auc: 0.9904 - prc: 0.9911 - val_loss: 0.0607 - val_tp: 60.0000 - val_fp: 527.0000 - val_tn: 44973.0000 - val_fn: 9.0000 - val_accuracy: 0.9882 - val_precision: 0.1022 - val_recall: 0.8696 - val_auc: 0.9550 - val_prc: 0.6405\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1298 - tp: 946.0000 - fp: 21.0000 - tn: 996.0000 - fn: 85.0000 - accuracy: 0.9482 - precision: 0.9783 - recall: 0.9176 - auc: 0.9896 - 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\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1201 - tp: 4742.0000 - fp: 115.0000 - tn: 4965.0000 - fn: 418.0000 - accuracy: 0.9479 - precision: 0.9763 - recall: 0.9190 - auc: 0.9914 - 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\b\b\b\r",
      "  8/278 [..............................] - ETA: 5s - loss: 0.1195 - tp: 7527.0000 - fp: 193.0000 - tn: 8010.0000 - fn: 654.0000 - accuracy: 0.9483 - precision: 0.9750 - recall: 0.9201 - auc: 0.9915 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1217 - tp: 10360.0000 - fp: 288.0000 - tn: 10982.0000 - fn: 898.0000 - accuracy: 0.9474 - precision: 0.9730 - recall: 0.9202 - auc: 0.9913 - 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\r",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1205 - tp: 13167.0000 - fp: 348.0000 - tn: 14008.0000 - fn: 1149.0000 - accuracy: 0.9478 - precision: 0.9743 - recall: 0.9197 - auc: 0.9914 - 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\r",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1204 - tp: 16006.0000 - fp: 410.0000 - tn: 16993.0000 - fn: 1407.0000 - accuracy: 0.9478 - precision: 0.9750 - recall: 0.9192 - auc: 0.9915 - 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\b\b\b\b\b\b\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1202 - tp: 18816.0000 - fp: 492.0000 - tn: 20007.0000 - fn: 1645.0000 - accuracy: 0.9478 - precision: 0.9745 - recall: 0.9196 - auc: 0.9915 - 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\b\b\b\b\b\b\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1205 - tp: 21675.0000 - fp: 571.0000 - tn: 22976.0000 - fn: 1882.0000 - accuracy: 0.9479 - precision: 0.9743 - recall: 0.9201 - auc: 0.9915 - 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\b\b\b\b\b\b\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.1202 - tp: 24509.0000 - fp: 645.0000 - tn: 25966.0000 - fn: 2128.0000 - accuracy: 0.9479 - precision: 0.9744 - recall: 0.9201 - auc: 0.9916 - 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\b\b\b\b\b\b\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.1193 - tp: 27366.0000 - fp: 704.0000 - tn: 28970.0000 - fn: 2352.0000 - accuracy: 0.9485 - precision: 0.9749 - recall: 0.9209 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1194 - tp: 30266.0000 - fp: 788.0000 - tn: 31908.0000 - fn: 2574.0000 - accuracy: 0.9487 - precision: 0.9746 - recall: 0.9216 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.1195 - tp: 33060.0000 - fp: 866.0000 - tn: 34942.0000 - fn: 2812.0000 - accuracy: 0.9487 - precision: 0.9745 - recall: 0.9216 - auc: 0.9916 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.1197 - tp: 35842.0000 - fp: 948.0000 - tn: 37989.0000 - fn: 3045.0000 - accuracy: 0.9487 - precision: 0.9742 - recall: 0.9217 - auc: 0.9916 - 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\b\b\b\b\b\b\r",
      " 41/278 [===>..........................] - ETA: 4s - loss: 0.1195 - tp: 38625.0000 - fp: 1018.0000 - tn: 41029.0000 - fn: 3296.0000 - accuracy: 0.9486 - precision: 0.9743 - recall: 0.9214 - auc: 0.9916 - 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\b\b\b\b\b\b\b\r",
      " 44/278 [===>..........................] - ETA: 4s - loss: 0.1192 - tp: 41485.0000 - fp: 1098.0000 - tn: 43999.0000 - fn: 3530.0000 - accuracy: 0.9486 - precision: 0.9742 - recall: 0.9216 - auc: 0.9916 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.1189 - tp: 44309.0000 - fp: 1157.0000 - tn: 47019.0000 - fn: 3771.0000 - accuracy: 0.9488 - precision: 0.9746 - recall: 0.9216 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1189 - tp: 47154.0000 - fp: 1233.0000 - tn: 50000.0000 - fn: 4013.0000 - accuracy: 0.9488 - precision: 0.9745 - recall: 0.9216 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1192 - tp: 49985.0000 - fp: 1310.0000 - tn: 53002.0000 - fn: 4247.0000 - accuracy: 0.9488 - precision: 0.9745 - recall: 0.9217 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1191 - tp: 52854.0000 - fp: 1391.0000 - tn: 55960.0000 - fn: 4483.0000 - accuracy: 0.9488 - precision: 0.9744 - recall: 0.9218 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 55726.0000 - fp: 1470.0000 - tn: 58921.0000 - fn: 4715.0000 - accuracy: 0.9488 - precision: 0.9743 - recall: 0.9220 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1194 - tp: 58573.0000 - fp: 1558.0000 - tn: 61885.0000 - fn: 4960.0000 - accuracy: 0.9487 - precision: 0.9741 - recall: 0.9219 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1195 - tp: 61438.0000 - fp: 1643.0000 - tn: 64833.0000 - fn: 5206.0000 - accuracy: 0.9486 - precision: 0.9740 - recall: 0.9219 - 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\b\b\b\b\b\b\b\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1197 - tp: 64213.0000 - fp: 1719.0000 - tn: 67884.0000 - fn: 5448.0000 - accuracy: 0.9485 - precision: 0.9739 - recall: 0.9218 - auc: 0.9916 - 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\b\b\b\b\b\b\b\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1197 - tp: 67036.0000 - fp: 1808.0000 - tn: 70869.0000 - fn: 5695.0000 - accuracy: 0.9484 - precision: 0.9737 - recall: 0.9217 - auc: 0.9916 - 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\b\b\b\b\b\b\b\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1197 - tp: 69903.0000 - fp: 1885.0000 - tn: 73826.0000 - fn: 5938.0000 - accuracy: 0.9484 - precision: 0.9737 - recall: 0.9217 - auc: 0.9916 - 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\b\b\b\b\b\b\b\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.1196 - tp: 72711.0000 - fp: 1957.0000 - tn: 76854.0000 - fn: 6174.0000 - accuracy: 0.9484 - precision: 0.9738 - recall: 0.9217 - 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\b\b\b\b\b\b\b\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1194 - tp: 75485.0000 - fp: 2037.0000 - tn: 79917.0000 - fn: 6401.0000 - accuracy: 0.9485 - precision: 0.9737 - recall: 0.9218 - 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\b\b\b\b\b\b\b\r",
      " 83/278 [=======>......................] - ETA: 3s - loss: 0.1195 - tp: 78323.0000 - fp: 2114.0000 - tn: 82917.0000 - fn: 6630.0000 - accuracy: 0.9486 - precision: 0.9737 - recall: 0.9220 - 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\b\b\b\b\b\b\b\r",
      " 86/278 [========>.....................] - ETA: 3s - loss: 0.1193 - tp: 81132.0000 - fp: 2197.0000 - tn: 85936.0000 - fn: 6863.0000 - accuracy: 0.9486 - precision: 0.9736 - recall: 0.9220 - 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\b\b\b\b\b\b\b\r",
      " 89/278 [========>.....................] - ETA: 3s - loss: 0.1193 - tp: 83970.0000 - fp: 2283.0000 - tn: 88921.0000 - fn: 7098.0000 - accuracy: 0.9485 - precision: 0.9735 - recall: 0.9221 - 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\b\b\b\b\b\b\b\r",
      " 92/278 [========>.....................] - ETA: 3s - loss: 0.1191 - tp: 86849.0000 - fp: 2348.0000 - tn: 91883.0000 - fn: 7336.0000 - accuracy: 0.9486 - precision: 0.9737 - recall: 0.9221 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.1190 - tp: 89696.0000 - fp: 2443.0000 - tn: 94872.0000 - fn: 7549.0000 - accuracy: 0.9486 - precision: 0.9735 - recall: 0.9224 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 92531.0000 - fp: 2519.0000 - tn: 97863.0000 - fn: 7791.0000 - accuracy: 0.9486 - precision: 0.9735 - recall: 0.9223 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1189 - tp: 95370.0000 - fp: 2609.0000 - tn: 100849.0000 - fn: 8020.0000 - accuracy: 0.9486 - precision: 0.9734 - recall: 0.9224 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 98224.0000 - fp: 2682.0000 - tn: 103836.0000 - fn: 8250.0000 - accuracy: 0.9487 - precision: 0.9734 - recall: 0.9225 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 101000.0000 - fp: 2758.0000 - tn: 106896.0000 - fn: 8482.0000 - accuracy: 0.9487 - precision: 0.9734 - recall: 0.9225 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 103870.0000 - fp: 2841.0000 - tn: 109843.0000 - fn: 8726.0000 - accuracy: 0.9487 - precision: 0.9734 - recall: 0.9225 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1191 - tp: 106634.0000 - fp: 2931.0000 - tn: 112883.0000 - fn: 8976.0000 - accuracy: 0.9485 - precision: 0.9732 - recall: 0.9224 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1191 - tp: 109538.0000 - fp: 3011.0000 - tn: 115809.0000 - fn: 9210.0000 - accuracy: 0.9486 - precision: 0.9732 - recall: 0.9224 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1191 - tp: 112338.0000 - fp: 3092.0000 - tn: 118841.0000 - fn: 9441.0000 - accuracy: 0.9486 - precision: 0.9732 - recall: 0.9225 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 115175.0000 - fp: 3163.0000 - tn: 121865.0000 - fn: 9653.0000 - accuracy: 0.9487 - precision: 0.9733 - recall: 0.9227 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 118039.0000 - fp: 3260.0000 - tn: 124822.0000 - fn: 9879.0000 - accuracy: 0.9487 - precision: 0.9731 - recall: 0.9228 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1190 - tp: 120842.0000 - fp: 3339.0000 - tn: 127854.0000 - fn: 10109.0000 - accuracy: 0.9487 - precision: 0.9731 - recall: 0.9228 - auc: 0.9917 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1189 - tp: 123671.0000 - fp: 3433.0000 - tn: 130856.0000 - fn: 10328.0000 - accuracy: 0.9487 - precision: 0.9730 - recall: 0.9229 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1188 - tp: 126510.0000 - fp: 3509.0000 - tn: 133855.0000 - fn: 10558.0000 - accuracy: 0.9487 - precision: 0.9730 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1186 - tp: 129374.0000 - fp: 3579.0000 - tn: 136828.0000 - fn: 10795.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1187 - tp: 132235.0000 - fp: 3649.0000 - tn: 139800.0000 - fn: 11036.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.1187 - tp: 135015.0000 - fp: 3727.0000 - tn: 142858.0000 - fn: 11264.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1187 - tp: 137847.0000 - fp: 3814.0000 - tn: 145840.0000 - fn: 11507.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1186 - tp: 140692.0000 - fp: 3887.0000 - tn: 148831.0000 - fn: 11742.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9230 - auc: 0.9918 - prc: 0.9921"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1185 - tp: 143509.0000 - fp: 3970.0000 - tn: 151855.0000 - fn: 11962.0000 - accuracy: 0.9488 - precision: 0.9731 - recall: 0.9231 - auc: 0.9918 - 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\b\b\b\r",
      "155/278 [===============>..............] - ETA: 2s - loss: 0.1185 - tp: 146390.0000 - fp: 4037.0000 - tn: 154810.0000 - fn: 12203.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9231 - auc: 0.9918 - 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\b\b\b\r",
      "158/278 [================>.............] - ETA: 2s - loss: 0.1183 - tp: 149184.0000 - fp: 4107.0000 - tn: 157838.0000 - fn: 12455.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "161/278 [================>.............] - ETA: 2s - loss: 0.1183 - tp: 152045.0000 - fp: 4186.0000 - tn: 160803.0000 - fn: 12694.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "164/278 [================>.............] - ETA: 2s - loss: 0.1182 - tp: 154882.0000 - fp: 4249.0000 - tn: 163800.0000 - fn: 12941.0000 - accuracy: 0.9488 - precision: 0.9733 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "167/278 [=================>............] - ETA: 2s - loss: 0.1183 - tp: 157726.0000 - fp: 4341.0000 - tn: 166761.0000 - fn: 13188.0000 - accuracy: 0.9487 - precision: 0.9732 - recall: 0.9228 - auc: 0.9919 - 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\b\b\b\r",
      "170/278 [=================>............] - ETA: 2s - loss: 0.1183 - tp: 160530.0000 - fp: 4428.0000 - tn: 169784.0000 - fn: 13418.0000 - accuracy: 0.9487 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "173/278 [=================>............] - ETA: 2s - loss: 0.1183 - tp: 163371.0000 - fp: 4506.0000 - tn: 172754.0000 - fn: 13673.0000 - accuracy: 0.9487 - precision: 0.9732 - recall: 0.9228 - auc: 0.9919 - 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\b\b\b\r",
      "176/278 [=================>............] - ETA: 2s - loss: 0.1182 - tp: 166213.0000 - fp: 4581.0000 - tn: 175755.0000 - fn: 13899.0000 - accuracy: 0.9487 - precision: 0.9732 - recall: 0.9228 - auc: 0.9919 - 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\b\b\b\r",
      "179/278 [==================>...........] - ETA: 2s - loss: 0.1182 - tp: 169070.0000 - fp: 4656.0000 - tn: 178726.0000 - fn: 14140.0000 - accuracy: 0.9487 - precision: 0.9732 - recall: 0.9228 - auc: 0.9919 - 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\b\b\b\r",
      "182/278 [==================>...........] - ETA: 1s - loss: 0.1181 - tp: 171903.0000 - fp: 4733.0000 - tn: 181744.0000 - fn: 14356.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "185/278 [==================>...........] - ETA: 1s - loss: 0.1181 - tp: 174763.0000 - fp: 4810.0000 - tn: 184717.0000 - fn: 14590.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "188/278 [===================>..........] - ETA: 1s - loss: 0.1181 - tp: 177573.0000 - fp: 4885.0000 - tn: 187738.0000 - fn: 14828.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9229 - auc: 0.9919 - 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\b\b\b\r",
      "191/278 [===================>..........] - ETA: 1s - loss: 0.1180 - tp: 180392.0000 - fp: 4964.0000 - tn: 190756.0000 - fn: 15056.0000 - accuracy: 0.9488 - precision: 0.9732 - recall: 0.9230 - auc: 0.9919 - 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\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.1179 - tp: 182302.0000 - fp: 5010.0000 - tn: 192766.0000 - fn: 15186.0000 - accuracy: 0.9489 - precision: 0.9733 - recall: 0.9231 - auc: 0.9919 - 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\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1179 - tp: 185102.0000 - fp: 5089.0000 - tn: 195803.0000 - fn: 15414.0000 - accuracy: 0.9489 - precision: 0.9732 - recall: 0.9231 - auc: 0.9919 - 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\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1179 - tp: 187866.0000 - fp: 5182.0000 - tn: 198855.0000 - fn: 15649.0000 - accuracy: 0.9489 - precision: 0.9732 - recall: 0.9231 - auc: 0.9919 - 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\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.1178 - tp: 190684.0000 - fp: 5264.0000 - tn: 201859.0000 - fn: 15889.0000 - accuracy: 0.9489 - precision: 0.9731 - recall: 0.9231 - auc: 0.9919 - 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\b\b\b\r",
      "205/278 [=====================>........] - ETA: 1s - loss: 0.1178 - tp: 193522.0000 - fp: 5341.0000 - tn: 204863.0000 - fn: 16114.0000 - accuracy: 0.9489 - precision: 0.9731 - recall: 0.9231 - auc: 0.9920 - 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\b\r",
      "208/278 [=====================>........] - ETA: 1s - loss: 0.1177 - tp: 196422.0000 - fp: 5402.0000 - tn: 207805.0000 - fn: 16355.0000 - accuracy: 0.9489 - precision: 0.9732 - recall: 0.9231 - auc: 0.9920 - 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\b\r",
      "211/278 [=====================>........] - ETA: 1s - loss: 0.1177 - tp: 199177.0000 - fp: 5488.0000 - tn: 210884.0000 - fn: 16579.0000 - accuracy: 0.9489 - precision: 0.9732 - recall: 0.9232 - auc: 0.9920 - 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\b\r",
      "214/278 [======================>.......] - ETA: 1s - loss: 0.1176 - tp: 202001.0000 - fp: 5573.0000 - tn: 213886.0000 - fn: 16812.0000 - accuracy: 0.9489 - precision: 0.9732 - recall: 0.9232 - auc: 0.9920 - 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\b\r",
      "217/278 [======================>.......] - ETA: 1s - loss: 0.1177 - tp: 204799.0000 - fp: 5660.0000 - tn: 216918.0000 - fn: 17039.0000 - accuracy: 0.9489 - precision: 0.9731 - recall: 0.9232 - auc: 0.9920 - 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\b\r",
      "220/278 [======================>.......] - ETA: 1s - loss: 0.1175 - tp: 207647.0000 - fp: 5724.0000 - tn: 219914.0000 - fn: 17275.0000 - accuracy: 0.9490 - precision: 0.9732 - recall: 0.9232 - auc: 0.9920 - 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\b\r",
      "223/278 [=======================>......] - ETA: 1s - loss: 0.1175 - tp: 210416.0000 - fp: 5821.0000 - tn: 222979.0000 - fn: 17488.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9233 - auc: 0.9920 - 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\b\r",
      "226/278 [=======================>......] - ETA: 1s - loss: 0.1174 - tp: 213242.0000 - fp: 5890.0000 - tn: 225997.0000 - fn: 17719.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9233 - auc: 0.9920 - 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\b\r",
      "229/278 [=======================>......] - ETA: 1s - loss: 0.1174 - tp: 216027.0000 - fp: 5979.0000 - tn: 229026.0000 - fn: 17960.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9232 - auc: 0.9920 - 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\b\r",
      "232/278 [========================>.....] - ETA: 0s - loss: 0.1173 - tp: 218869.0000 - fp: 6056.0000 - tn: 232028.0000 - fn: 18183.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9233 - auc: 0.9920 - 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\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1172 - tp: 221712.0000 - fp: 6123.0000 - tn: 235021.0000 - fn: 18424.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9233 - auc: 0.9920 - 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\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1171 - tp: 224487.0000 - fp: 6208.0000 - tn: 238091.0000 - fn: 18638.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9233 - auc: 0.9921 - 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\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.1171 - tp: 226414.0000 - fp: 6257.0000 - tn: 240060.0000 - fn: 18789.0000 - accuracy: 0.9490 - precision: 0.9731 - recall: 0.9234 - auc: 0.9921 - 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\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.1170 - tp: 229219.0000 - fp: 6331.0000 - tn: 243098.0000 - fn: 19016.0000 - accuracy: 0.9491 - precision: 0.9731 - recall: 0.9234 - auc: 0.9921 - 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",
      "245/278 [=========================>....] - ETA: 0s - loss: 0.1170 - tp: 231089.0000 - fp: 6380.0000 - tn: 245127.0000 - fn: 19164.0000 - accuracy: 0.9491 - precision: 0.9731 - recall: 0.9234 - auc: 0.9921 - 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",
      "248/278 [=========================>....] - ETA: 0s - loss: 0.1169 - tp: 233905.0000 - fp: 6465.0000 - tn: 248131.0000 - fn: 19403.0000 - accuracy: 0.9491 - precision: 0.9731 - recall: 0.9234 - auc: 0.9921 - 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",
      "251/278 [==========================>...] - ETA: 0s - loss: 0.1168 - tp: 236758.0000 - fp: 6545.0000 - tn: 251126.0000 - fn: 19619.0000 - accuracy: 0.9491 - precision: 0.9731 - recall: 0.9235 - auc: 0.9921 - 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",
      "254/278 [==========================>...] - ETA: 0s - loss: 0.1168 - tp: 239614.0000 - fp: 6611.0000 - tn: 254123.0000 - fn: 19844.0000 - accuracy: 0.9491 - precision: 0.9732 - recall: 0.9235 - auc: 0.9921 - 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",
      "257/278 [==========================>...] - ETA: 0s - loss: 0.1167 - tp: 242454.0000 - fp: 6703.0000 - tn: 257128.0000 - fn: 20051.0000 - accuracy: 0.9492 - precision: 0.9731 - recall: 0.9236 - auc: 0.9921 - 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",
      "260/278 [===========================>..] - ETA: 0s - loss: 0.1167 - tp: 245309.0000 - fp: 6794.0000 - tn: 260096.0000 - fn: 20281.0000 - accuracy: 0.9492 - precision: 0.9731 - recall: 0.9236 - auc: 0.9921 - 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",
      "263/278 [===========================>..] - ETA: 0s - loss: 0.1167 - tp: 248187.0000 - fp: 6870.0000 - tn: 263069.0000 - fn: 20498.0000 - accuracy: 0.9492 - precision: 0.9731 - recall: 0.9237 - auc: 0.9921 - 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",
      "266/278 [===========================>..] - ETA: 0s - loss: 0.1166 - tp: 251025.0000 - fp: 6949.0000 - tn: 266066.0000 - fn: 20728.0000 - accuracy: 0.9492 - precision: 0.9731 - recall: 0.9237 - auc: 0.9922 - 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",
      "269/278 [============================>.] - ETA: 0s - loss: 0.1166 - tp: 253899.0000 - fp: 7024.0000 - tn: 269047.0000 - fn: 20942.0000 - accuracy: 0.9492 - precision: 0.9731 - recall: 0.9238 - auc: 0.9922 - 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",
      "272/278 [============================>.] - ETA: 0s - loss: 0.1165 - tp: 256732.0000 - fp: 7105.0000 - tn: 272055.0000 - fn: 21164.0000 - accuracy: 0.9493 - precision: 0.9731 - recall: 0.9238 - auc: 0.9922 - 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",
      "275/278 [============================>.] - ETA: 0s - loss: 0.1164 - tp: 259572.0000 - fp: 7186.0000 - tn: 275068.0000 - fn: 21374.0000 - accuracy: 0.9493 - precision: 0.9731 - recall: 0.9239 - auc: 0.9922 - 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",
      "278/278 [==============================] - ETA: 0s - loss: 0.1164 - tp: 262446.0000 - fp: 7264.0000 - tn: 278031.0000 - fn: 21603.0000 - accuracy: 0.9493 - precision: 0.9731 - recall: 0.9239 - auc: 0.9922 - 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",
      "278/278 [==============================] - 6s 21ms/step - loss: 0.1164 - tp: 262446.0000 - fp: 7264.0000 - tn: 278031.0000 - fn: 21603.0000 - accuracy: 0.9493 - precision: 0.9731 - recall: 0.9239 - auc: 0.9922 - prc: 0.9924 - val_loss: 0.0561 - val_tp: 60.0000 - val_fp: 544.0000 - val_tn: 44956.0000 - val_fn: 9.0000 - val_accuracy: 0.9879 - val_precision: 0.0993 - val_recall: 0.8696 - val_auc: 0.9554 - val_prc: 0.6181\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1040 - tp: 964.0000 - fp: 18.0000 - tn: 987.0000 - fn: 79.0000 - accuracy: 0.9526 - precision: 0.9817 - recall: 0.9243 - auc: 0.9940 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1140 - tp: 4698.0000 - fp: 121.0000 - tn: 5018.0000 - fn: 403.0000 - accuracy: 0.9488 - precision: 0.9749 - recall: 0.9210 - auc: 0.9927 - 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",
      "  8/278 [..............................] - ETA: 4s - loss: 0.1143 - tp: 7534.0000 - fp: 208.0000 - tn: 8004.0000 - fn: 638.0000 - accuracy: 0.9484 - precision: 0.9731 - recall: 0.9219 - auc: 0.9925 - 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\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1147 - tp: 10386.0000 - fp: 289.0000 - tn: 10981.0000 - fn: 872.0000 - accuracy: 0.9485 - precision: 0.9729 - recall: 0.9225 - auc: 0.9925 - 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",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1144 - tp: 13342.0000 - fp: 365.0000 - tn: 13868.0000 - fn: 1097.0000 - accuracy: 0.9490 - precision: 0.9734 - recall: 0.9240 - auc: 0.9925 - 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",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1133 - tp: 16127.0000 - fp: 450.0000 - tn: 16911.0000 - fn: 1328.0000 - accuracy: 0.9489 - precision: 0.9729 - recall: 0.9239 - auc: 0.9927 - 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\r",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1133 - tp: 18960.0000 - fp: 543.0000 - tn: 19897.0000 - fn: 1560.0000 - accuracy: 0.9487 - precision: 0.9722 - recall: 0.9240 - auc: 0.9927 - 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\r",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1132 - tp: 21808.0000 - fp: 622.0000 - tn: 22884.0000 - fn: 1790.0000 - accuracy: 0.9488 - precision: 0.9723 - recall: 0.9241 - auc: 0.9926 - 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\r",
      " 26/278 [=>............................] - ETA: 5s - loss: 0.1132 - tp: 24641.0000 - fp: 695.0000 - tn: 25900.0000 - fn: 2012.0000 - accuracy: 0.9492 - precision: 0.9726 - recall: 0.9245 - auc: 0.9927 - 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\r",
      " 29/278 [==>...........................] - ETA: 5s - loss: 0.1127 - tp: 27438.0000 - fp: 778.0000 - tn: 28937.0000 - fn: 2239.0000 - accuracy: 0.9492 - precision: 0.9724 - recall: 0.9246 - auc: 0.9927 - 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\r",
      " 32/278 [==>...........................] - ETA: 4s - loss: 0.1128 - tp: 30309.0000 - fp: 844.0000 - tn: 31928.0000 - fn: 2455.0000 - accuracy: 0.9497 - precision: 0.9729 - recall: 0.9251 - auc: 0.9928 - 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\r",
      " 35/278 [==>...........................] - ETA: 4s - loss: 0.1130 - tp: 33137.0000 - fp: 925.0000 - tn: 34920.0000 - fn: 2698.0000 - accuracy: 0.9495 - precision: 0.9728 - recall: 0.9247 - auc: 0.9927 - 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\r",
      " 38/278 [===>..........................] - ETA: 4s - loss: 0.1127 - tp: 35985.0000 - fp: 1000.0000 - tn: 37929.0000 - fn: 2910.0000 - accuracy: 0.9498 - precision: 0.9730 - recall: 0.9252 - auc: 0.9928 - 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\r",
      " 41/278 [===>..........................] - ETA: 4s - loss: 0.1128 - tp: 38861.0000 - fp: 1067.0000 - tn: 40893.0000 - fn: 3147.0000 - accuracy: 0.9498 - precision: 0.9733 - recall: 0.9251 - auc: 0.9927 - 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",
      " 44/278 [===>..........................] - ETA: 4s - loss: 0.1124 - tp: 41723.0000 - fp: 1136.0000 - tn: 43886.0000 - fn: 3367.0000 - accuracy: 0.9500 - precision: 0.9735 - recall: 0.9253 - auc: 0.9928 - 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\r",
      " 47/278 [====>.........................] - ETA: 4s - loss: 0.1126 - tp: 44547.0000 - fp: 1236.0000 - tn: 46887.0000 - fn: 3586.0000 - accuracy: 0.9499 - precision: 0.9730 - recall: 0.9255 - auc: 0.9927 - 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",
      " 50/278 [====>.........................] - ETA: 4s - loss: 0.1122 - tp: 47397.0000 - fp: 1303.0000 - tn: 49896.0000 - fn: 3804.0000 - accuracy: 0.9501 - precision: 0.9732 - recall: 0.9257 - auc: 0.9928 - 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\r",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.1121 - tp: 50303.0000 - fp: 1391.0000 - tn: 52837.0000 - fn: 4013.0000 - accuracy: 0.9502 - precision: 0.9731 - recall: 0.9261 - auc: 0.9928 - 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\r",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1124 - tp: 53118.0000 - fp: 1477.0000 - tn: 55846.0000 - fn: 4247.0000 - accuracy: 0.9501 - precision: 0.9729 - recall: 0.9260 - auc: 0.9928 - 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\r",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1122 - tp: 56005.0000 - fp: 1545.0000 - tn: 58805.0000 - fn: 4477.0000 - accuracy: 0.9502 - precision: 0.9732 - recall: 0.9260 - auc: 0.9928 - 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\r",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1122 - tp: 58864.0000 - fp: 1632.0000 - tn: 61769.0000 - fn: 4711.0000 - accuracy: 0.9500 - precision: 0.9730 - recall: 0.9259 - auc: 0.9928 - 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\r",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.1121 - tp: 61766.0000 - fp: 1708.0000 - tn: 64709.0000 - fn: 4937.0000 - accuracy: 0.9501 - precision: 0.9731 - recall: 0.9260 - auc: 0.9928 - 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\r",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1121 - tp: 64620.0000 - fp: 1796.0000 - tn: 67703.0000 - fn: 5145.0000 - accuracy: 0.9502 - precision: 0.9730 - recall: 0.9263 - auc: 0.9928 - 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\r",
      " 71/278 [======>.......................] - ETA: 4s - loss: 0.1119 - tp: 67470.0000 - fp: 1862.0000 - tn: 70710.0000 - fn: 5366.0000 - accuracy: 0.9503 - precision: 0.9731 - recall: 0.9263 - auc: 0.9928 - 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\r",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1119 - tp: 70299.0000 - fp: 1931.0000 - tn: 73716.0000 - fn: 5606.0000 - accuracy: 0.9503 - precision: 0.9733 - recall: 0.9261 - auc: 0.9928 - 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\r",
      " 77/278 [=======>......................] - ETA: 4s - loss: 0.1120 - tp: 73240.0000 - fp: 2025.0000 - tn: 76614.0000 - fn: 5817.0000 - accuracy: 0.9503 - precision: 0.9731 - recall: 0.9264 - auc: 0.9928 - 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\r",
      " 79/278 [=======>......................] - ETA: 4s - loss: 0.1120 - tp: 75161.0000 - fp: 2071.0000 - tn: 78595.0000 - fn: 5965.0000 - accuracy: 0.9503 - precision: 0.9732 - recall: 0.9265 - auc: 0.9928 - 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\r",
      " 82/278 [=======>......................] - ETA: 4s - loss: 0.1120 - tp: 78026.0000 - fp: 2148.0000 - tn: 81579.0000 - fn: 6183.0000 - accuracy: 0.9504 - precision: 0.9732 - recall: 0.9266 - auc: 0.9928 - 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\r",
      " 85/278 [========>.....................] - ETA: 4s - loss: 0.1118 - tp: 80860.0000 - fp: 2226.0000 - tn: 84604.0000 - fn: 6390.0000 - accuracy: 0.9505 - precision: 0.9732 - recall: 0.9268 - auc: 0.9929 - 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\r",
      " 88/278 [========>.....................] - ETA: 3s - loss: 0.1118 - tp: 83673.0000 - fp: 2305.0000 - tn: 87633.0000 - fn: 6613.0000 - accuracy: 0.9505 - precision: 0.9732 - recall: 0.9268 - auc: 0.9929 - 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\r",
      " 91/278 [========>.....................] - ETA: 3s - loss: 0.1118 - tp: 86505.0000 - fp: 2387.0000 - tn: 90631.0000 - fn: 6845.0000 - accuracy: 0.9505 - precision: 0.9731 - recall: 0.9267 - auc: 0.9929 - 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\r",
      " 94/278 [=========>....................] - ETA: 3s - loss: 0.1118 - tp: 89367.0000 - fp: 2473.0000 - tn: 93603.0000 - fn: 7069.0000 - accuracy: 0.9504 - precision: 0.9731 - recall: 0.9267 - auc: 0.9929 - 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\r",
      " 97/278 [=========>....................] - ETA: 3s - loss: 0.1118 - tp: 92236.0000 - fp: 2563.0000 - tn: 96563.0000 - fn: 7294.0000 - accuracy: 0.9504 - precision: 0.9730 - recall: 0.9267 - auc: 0.9929 - 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\r",
      "100/278 [=========>....................] - ETA: 3s - loss: 0.1118 - tp: 95131.0000 - fp: 2639.0000 - tn: 99517.0000 - fn: 7513.0000 - accuracy: 0.9504 - precision: 0.9730 - recall: 0.9268 - auc: 0.9929 - 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\r",
      "103/278 [==========>...................] - ETA: 3s - loss: 0.1117 - tp: 97994.0000 - fp: 2717.0000 - tn: 102503.0000 - fn: 7730.0000 - accuracy: 0.9505 - precision: 0.9730 - recall: 0.9269 - auc: 0.9929 - 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\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.1115 - tp: 100811.0000 - fp: 2792.0000 - tn: 105532.0000 - fn: 7953.0000 - accuracy: 0.9505 - precision: 0.9731 - recall: 0.9269 - auc: 0.9929 - 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\r",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.1114 - tp: 103675.0000 - fp: 2870.0000 - tn: 108513.0000 - fn: 8174.0000 - accuracy: 0.9505 - precision: 0.9731 - recall: 0.9269 - auc: 0.9929 - 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\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.1114 - tp: 106481.0000 - fp: 2959.0000 - tn: 111531.0000 - fn: 8405.0000 - accuracy: 0.9505 - precision: 0.9730 - recall: 0.9268 - auc: 0.9929 - 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\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.1114 - tp: 109330.0000 - fp: 3026.0000 - tn: 114514.0000 - fn: 8650.0000 - accuracy: 0.9504 - precision: 0.9731 - recall: 0.9267 - auc: 0.9929 - 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\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1113 - tp: 112207.0000 - fp: 3107.0000 - tn: 117485.0000 - fn: 8865.0000 - accuracy: 0.9505 - precision: 0.9731 - recall: 0.9268 - auc: 0.9929 - 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\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1113 - tp: 115084.0000 - fp: 3180.0000 - tn: 120450.0000 - fn: 9094.0000 - accuracy: 0.9505 - precision: 0.9731 - recall: 0.9268 - auc: 0.9929 - 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\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.1112 - tp: 117896.0000 - fp: 3250.0000 - tn: 123492.0000 - fn: 9314.0000 - accuracy: 0.9505 - precision: 0.9732 - recall: 0.9268 - auc: 0.9929 - 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\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1112 - tp: 120746.0000 - fp: 3333.0000 - tn: 126491.0000 - fn: 9526.0000 - accuracy: 0.9506 - precision: 0.9731 - recall: 0.9269 - auc: 0.9929 - 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\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1114 - tp: 123646.0000 - fp: 3428.0000 - tn: 129422.0000 - fn: 9744.0000 - accuracy: 0.9505 - precision: 0.9730 - recall: 0.9270 - auc: 0.9929 - 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\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.1116 - tp: 126398.0000 - fp: 3509.0000 - tn: 132516.0000 - fn: 9961.0000 - accuracy: 0.9505 - precision: 0.9730 - recall: 0.9270 - auc: 0.9929 - 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\r",
      "136/278 [=============>................] - ETA: 2s - loss: 0.1114 - tp: 129193.0000 - fp: 3584.0000 - tn: 135571.0000 - fn: 10180.0000 - accuracy: 0.9506 - precision: 0.9730 - recall: 0.9270 - auc: 0.9929 - 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",
      "139/278 [==============>...............] - ETA: 2s - loss: 0.1114 - tp: 132026.0000 - fp: 3669.0000 - tn: 138573.0000 - fn: 10404.0000 - accuracy: 0.9506 - precision: 0.9730 - recall: 0.9270 - auc: 0.9929 - 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",
      "142/278 [==============>...............] - ETA: 2s - loss: 0.1112 - tp: 134897.0000 - fp: 3741.0000 - tn: 141568.0000 - fn: 10610.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9271 - auc: 0.9929 - 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",
      "145/278 [==============>...............] - ETA: 2s - loss: 0.1112 - tp: 137712.0000 - fp: 3824.0000 - tn: 144595.0000 - fn: 10829.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9271 - auc: 0.9930 - 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",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1112 - tp: 140578.0000 - fp: 3895.0000 - tn: 147588.0000 - fn: 11043.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9272 - auc: 0.9930 - 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",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1113 - tp: 143435.0000 - fp: 3965.0000 - tn: 150563.0000 - fn: 11285.0000 - accuracy: 0.9507 - precision: 0.9731 - recall: 0.9271 - auc: 0.9930 - 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",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1112 - tp: 146289.0000 - fp: 4052.0000 - tn: 153541.0000 - fn: 11510.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9271 - auc: 0.9930 - 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",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.1112 - tp: 149200.0000 - fp: 4134.0000 - tn: 156458.0000 - fn: 11744.0000 - accuracy: 0.9506 - precision: 0.9730 - recall: 0.9270 - auc: 0.9930 - 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",
      "160/278 [================>.............] - ETA: 2s - loss: 0.1112 - tp: 152020.0000 - fp: 4216.0000 - tn: 159485.0000 - fn: 11959.0000 - accuracy: 0.9506 - precision: 0.9730 - recall: 0.9271 - auc: 0.9930 - 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",
      "163/278 [================>.............] - ETA: 2s - loss: 0.1111 - tp: 154867.0000 - fp: 4284.0000 - tn: 162499.0000 - fn: 12174.0000 - accuracy: 0.9507 - precision: 0.9731 - recall: 0.9271 - auc: 0.9930 - 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",
      "166/278 [================>.............] - ETA: 2s - loss: 0.1112 - tp: 157702.0000 - fp: 4367.0000 - tn: 165503.0000 - fn: 12396.0000 - accuracy: 0.9507 - precision: 0.9731 - recall: 0.9271 - auc: 0.9930 - 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",
      "169/278 [=================>............] - ETA: 2s - loss: 0.1111 - tp: 160495.0000 - fp: 4446.0000 - tn: 168559.0000 - fn: 12612.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9271 - auc: 0.9930 - 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",
      "172/278 [=================>............] - ETA: 2s - loss: 0.1110 - tp: 163353.0000 - fp: 4528.0000 - tn: 171554.0000 - fn: 12821.0000 - accuracy: 0.9507 - precision: 0.9730 - recall: 0.9272 - auc: 0.9930 - 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",
      "175/278 [=================>............] - ETA: 2s - loss: 0.1108 - tp: 166254.0000 - fp: 4597.0000 - tn: 174523.0000 - fn: 13026.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9273 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1107 - tp: 169130.0000 - fp: 4666.0000 - tn: 177495.0000 - fn: 13253.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9273 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1107 - tp: 171968.0000 - fp: 4748.0000 - tn: 180491.0000 - fn: 13481.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9273 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1106 - tp: 174809.0000 - fp: 4814.0000 - tn: 183492.0000 - fn: 13717.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1106 - tp: 177639.0000 - fp: 4901.0000 - tn: 186491.0000 - fn: 13945.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.1106 - tp: 179597.0000 - fp: 4951.0000 - tn: 188432.0000 - fn: 14092.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 182462.0000 - fp: 5032.0000 - tn: 191388.0000 - fn: 14334.0000 - accuracy: 0.9507 - precision: 0.9732 - recall: 0.9272 - auc: 0.9930 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1105 - tp: 185332.0000 - fp: 5110.0000 - tn: 194367.0000 - fn: 14551.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 188146.0000 - fp: 5188.0000 - tn: 197398.0000 - fn: 14772.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 191016.0000 - fp: 5265.0000 - tn: 200380.0000 - fn: 14987.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 193876.0000 - fp: 5353.0000 - tn: 203373.0000 - fn: 15190.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1105 - tp: 196668.0000 - fp: 5424.0000 - tn: 206422.0000 - fn: 15422.0000 - accuracy: 0.9508 - precision: 0.9732 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1107 - tp: 199496.0000 - fp: 5521.0000 - tn: 209409.0000 - fn: 15654.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 202352.0000 - fp: 5600.0000 - tn: 212389.0000 - fn: 15883.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9272 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 204228.0000 - fp: 5657.0000 - tn: 214417.0000 - fn: 16018.0000 - accuracy: 0.9508 - precision: 0.9730 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1106 - tp: 207105.0000 - fp: 5742.0000 - tn: 217379.0000 - fn: 16238.0000 - accuracy: 0.9508 - precision: 0.9730 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1105 - tp: 209944.0000 - fp: 5808.0000 - tn: 220389.0000 - fn: 16467.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1105 - tp: 212857.0000 - fp: 5879.0000 - tn: 223338.0000 - fn: 16678.0000 - accuracy: 0.9508 - precision: 0.9731 - recall: 0.9273 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1104 - tp: 215725.0000 - fp: 5951.0000 - tn: 226339.0000 - fn: 16881.0000 - accuracy: 0.9509 - precision: 0.9732 - recall: 0.9274 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1103 - tp: 218548.0000 - fp: 6013.0000 - tn: 229393.0000 - fn: 17086.0000 - accuracy: 0.9510 - precision: 0.9732 - recall: 0.9275 - auc: 0.9931 - prc: 0.9932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.1102 - tp: 221430.0000 - fp: 6077.0000 - tn: 232366.0000 - fn: 17311.0000 - accuracy: 0.9510 - precision: 0.9733 - recall: 0.9275 - auc: 0.9931 - 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\b\b\b\b\r",
      "235/278 [========================>.....] - ETA: 0s - loss: 0.1102 - tp: 223295.0000 - fp: 6132.0000 - tn: 234387.0000 - fn: 17466.0000 - accuracy: 0.9510 - precision: 0.9733 - recall: 0.9275 - auc: 0.9931 - 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\b\b\b\b\r",
      "238/278 [========================>.....] - ETA: 0s - loss: 0.1101 - tp: 226138.0000 - fp: 6209.0000 - tn: 237392.0000 - fn: 17685.0000 - accuracy: 0.9510 - precision: 0.9733 - recall: 0.9275 - auc: 0.9931 - 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\b\b\b\b\r",
      "240/278 [========================>.....] - ETA: 0s - loss: 0.1101 - tp: 228057.0000 - fp: 6264.0000 - tn: 239385.0000 - fn: 17814.0000 - accuracy: 0.9510 - precision: 0.9733 - recall: 0.9275 - auc: 0.9932 - 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\b\b\b\b\r",
      "242/278 [=========================>....] - ETA: 0s - loss: 0.1100 - tp: 230013.0000 - fp: 6300.0000 - tn: 241347.0000 - fn: 17956.0000 - accuracy: 0.9511 - precision: 0.9733 - recall: 0.9276 - auc: 0.9932 - 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\b\b\b\b\r",
      "244/278 [=========================>....] - ETA: 0s - loss: 0.1101 - tp: 231978.0000 - fp: 6357.0000 - tn: 243286.0000 - fn: 18091.0000 - accuracy: 0.9511 - precision: 0.9733 - recall: 0.9277 - auc: 0.9932 - 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\b\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.1100 - tp: 233886.0000 - fp: 6416.0000 - tn: 245281.0000 - fn: 18225.0000 - accuracy: 0.9511 - precision: 0.9733 - recall: 0.9277 - auc: 0.9932 - 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\b\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.1100 - tp: 236755.0000 - fp: 6491.0000 - tn: 248253.0000 - fn: 18453.0000 - accuracy: 0.9511 - precision: 0.9733 - recall: 0.9277 - auc: 0.9932 - 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\b\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1099 - tp: 239595.0000 - fp: 6558.0000 - tn: 251271.0000 - fn: 18672.0000 - accuracy: 0.9511 - precision: 0.9734 - recall: 0.9277 - auc: 0.9932 - 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\b\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1098 - tp: 242466.0000 - fp: 6635.0000 - tn: 254255.0000 - fn: 18884.0000 - accuracy: 0.9511 - precision: 0.9734 - recall: 0.9277 - auc: 0.9932 - 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\b\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1097 - tp: 245342.0000 - fp: 6709.0000 - tn: 257234.0000 - fn: 19099.0000 - accuracy: 0.9512 - precision: 0.9734 - recall: 0.9278 - auc: 0.9932 - 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\b\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1097 - tp: 248303.0000 - fp: 6785.0000 - tn: 260122.0000 - fn: 19318.0000 - accuracy: 0.9512 - precision: 0.9734 - recall: 0.9278 - auc: 0.9932 - 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\b\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1097 - tp: 251128.0000 - fp: 6871.0000 - tn: 263150.0000 - fn: 19523.0000 - accuracy: 0.9512 - precision: 0.9734 - recall: 0.9279 - auc: 0.9932 - 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\b\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1097 - tp: 253991.0000 - fp: 6959.0000 - tn: 266118.0000 - fn: 19748.0000 - accuracy: 0.9512 - precision: 0.9733 - recall: 0.9279 - auc: 0.9932 - 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\b\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1097 - tp: 256809.0000 - fp: 7046.0000 - tn: 269134.0000 - fn: 19971.0000 - accuracy: 0.9511 - precision: 0.9733 - recall: 0.9278 - auc: 0.9932 - 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\b\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1095 - tp: 259747.0000 - fp: 7097.0000 - tn: 272075.0000 - fn: 20185.0000 - accuracy: 0.9512 - precision: 0.9734 - recall: 0.9279 - auc: 0.9932 - 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\b\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1095 - tp: 262647.0000 - fp: 7167.0000 - tn: 275030.0000 - fn: 20404.0000 - accuracy: 0.9512 - precision: 0.9734 - recall: 0.9279 - auc: 0.9932 - 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\b\b\b\b\r",
      "278/278 [==============================] - 6s 22ms/step - loss: 0.1095 - tp: 264558.0000 - fp: 7213.0000 - tn: 277018.0000 - fn: 20555.0000 - accuracy: 0.9512 - precision: 0.9735 - recall: 0.9279 - auc: 0.9932 - prc: 0.9934 - val_loss: 0.0521 - val_tp: 60.0000 - val_fp: 535.0000 - val_tn: 44965.0000 - val_fn: 9.0000 - val_accuracy: 0.9881 - val_precision: 0.1008 - val_recall: 0.8696 - val_auc: 0.9569 - val_prc: 0.6182\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.1098 - tp: 947.0000 - fp: 25.0000 - tn: 997.0000 - fn: 79.0000 - accuracy: 0.9492 - precision: 0.9743 - recall: 0.9230 - auc: 0.9931 - 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\r",
      "  5/278 [..............................] - ETA: 4s - loss: 0.1039 - tp: 4788.0000 - fp: 133.0000 - tn: 4946.0000 - fn: 373.0000 - accuracy: 0.9506 - precision: 0.9730 - recall: 0.9277 - auc: 0.9940 - 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\r",
      "  8/278 [..............................] - ETA: 4s - loss: 0.1053 - tp: 7630.0000 - fp: 218.0000 - tn: 7946.0000 - fn: 590.0000 - accuracy: 0.9507 - precision: 0.9722 - recall: 0.9282 - auc: 0.9937 - 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\r",
      " 11/278 [>.............................] - ETA: 5s - loss: 0.1045 - tp: 10463.0000 - fp: 289.0000 - tn: 10974.0000 - fn: 802.0000 - accuracy: 0.9516 - precision: 0.9731 - recall: 0.9288 - auc: 0.9938 - 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",
      " 14/278 [>.............................] - ETA: 5s - loss: 0.1039 - tp: 13259.0000 - fp: 378.0000 - tn: 14035.0000 - fn: 1000.0000 - accuracy: 0.9519 - precision: 0.9723 - recall: 0.9299 - auc: 0.9939 - 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",
      " 17/278 [>.............................] - ETA: 5s - loss: 0.1046 - tp: 16167.0000 - fp: 455.0000 - tn: 16963.0000 - fn: 1231.0000 - accuracy: 0.9516 - precision: 0.9726 - recall: 0.9292 - auc: 0.9939 - 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",
      " 20/278 [=>............................] - ETA: 5s - loss: 0.1049 - tp: 19086.0000 - fp: 541.0000 - tn: 19897.0000 - fn: 1436.0000 - accuracy: 0.9517 - precision: 0.9724 - recall: 0.9300 - auc: 0.9938 - 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",
      " 23/278 [=>............................] - ETA: 5s - loss: 0.1053 - tp: 21977.0000 - fp: 623.0000 - tn: 22841.0000 - fn: 1663.0000 - accuracy: 0.9515 - precision: 0.9724 - recall: 0.9297 - auc: 0.9938 - 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: 0.1050 - tp: 24788.0000 - fp: 697.0000 - tn: 25904.0000 - fn: 1859.0000 - accuracy: 0.9520 - precision: 0.9727 - recall: 0.9302 - auc: 0.9938 - 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",
      " 29/278 [==>...........................] - ETA: 4s - loss: 0.1058 - tp: 27611.0000 - fp: 787.0000 - tn: 28924.0000 - fn: 2070.0000 - accuracy: 0.9519 - precision: 0.9723 - recall: 0.9303 - auc: 0.9937 - 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",
      " 32/278 [==>...........................] - ETA: 4s - loss: 0.1059 - tp: 30432.0000 - fp: 871.0000 - tn: 31954.0000 - fn: 2279.0000 - accuracy: 0.9519 - precision: 0.9722 - recall: 0.9303 - auc: 0.9937 - 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",
      " 35/278 [==>...........................] - ETA: 4s - loss: 0.1064 - tp: 33335.0000 - fp: 954.0000 - tn: 34891.0000 - fn: 2500.0000 - accuracy: 0.9518 - precision: 0.9722 - recall: 0.9302 - auc: 0.9936 - 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",
      " 38/278 [===>..........................] - ETA: 4s - loss: 0.1065 - tp: 36132.0000 - fp: 1031.0000 - tn: 37948.0000 - fn: 2713.0000 - accuracy: 0.9519 - precision: 0.9723 - recall: 0.9302 - auc: 0.9936 - 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",
      " 41/278 [===>..........................] - ETA: 4s - loss: 0.1066 - tp: 39006.0000 - fp: 1106.0000 - tn: 40938.0000 - fn: 2918.0000 - accuracy: 0.9521 - precision: 0.9724 - recall: 0.9304 - auc: 0.9936 - 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",
      " 44/278 [===>..........................] - ETA: 4s - loss: 0.1068 - tp: 41912.0000 - fp: 1202.0000 - tn: 43876.0000 - fn: 3122.0000 - accuracy: 0.9520 - precision: 0.9721 - recall: 0.9307 - auc: 0.9936 - 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",
      " 47/278 [====>.........................] - ETA: 4s - loss: 0.1066 - tp: 44835.0000 - fp: 1279.0000 - tn: 46802.0000 - fn: 3340.0000 - accuracy: 0.9520 - precision: 0.9723 - recall: 0.9307 - auc: 0.9936 - 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",
      " 50/278 [====>.........................] - ETA: 4s - loss: 0.1064 - tp: 47761.0000 - fp: 1351.0000 - tn: 49737.0000 - fn: 3551.0000 - accuracy: 0.9521 - precision: 0.9725 - recall: 0.9308 - auc: 0.9936 - 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",
      " 53/278 [====>.........................] - ETA: 4s - loss: 0.1063 - tp: 50612.0000 - fp: 1429.0000 - tn: 52740.0000 - fn: 3763.0000 - accuracy: 0.9522 - precision: 0.9725 - recall: 0.9308 - auc: 0.9936 - 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",
      " 56/278 [=====>........................] - ETA: 4s - loss: 0.1061 - tp: 53412.0000 - fp: 1529.0000 - tn: 55773.0000 - fn: 3974.0000 - accuracy: 0.9520 - precision: 0.9722 - recall: 0.9307 - auc: 0.9936 - 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",
      " 59/278 [=====>........................] - ETA: 4s - loss: 0.1064 - tp: 56231.0000 - fp: 1623.0000 - tn: 58782.0000 - fn: 4196.0000 - accuracy: 0.9518 - precision: 0.9719 - recall: 0.9306 - auc: 0.9936 - 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",
      " 62/278 [=====>........................] - ETA: 4s - loss: 0.1062 - tp: 59220.0000 - fp: 1707.0000 - tn: 61663.0000 - fn: 4386.0000 - accuracy: 0.9520 - precision: 0.9720 - recall: 0.9310 - auc: 0.9936 - 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",
      " 65/278 [======>.......................] - ETA: 4s - loss: 0.1061 - tp: 62147.0000 - fp: 1786.0000 - tn: 64610.0000 - fn: 4577.0000 - accuracy: 0.9522 - precision: 0.9721 - recall: 0.9314 - auc: 0.9936 - 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",
      " 68/278 [======>.......................] - ETA: 4s - loss: 0.1060 - tp: 64898.0000 - fp: 1867.0000 - tn: 67712.0000 - fn: 4787.0000 - accuracy: 0.9522 - precision: 0.9720 - recall: 0.9313 - auc: 0.9936 - prc: 0.9936"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1059 - tp: 67748.0000 - fp: 1943.0000 - tn: 70727.0000 - fn: 4990.0000 - accuracy: 0.9523 - precision: 0.9721 - recall: 0.9314 - auc: 0.9937 - 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",
      " 74/278 [======>.......................] - ETA: 4s - loss: 0.1058 - tp: 70666.0000 - fp: 2009.0000 - tn: 73657.0000 - fn: 5220.0000 - accuracy: 0.9523 - precision: 0.9724 - recall: 0.9312 - auc: 0.9937 - prc: 0.9937"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1059 - tp: 73509.0000 - fp: 2087.0000 - tn: 76678.0000 - fn: 5422.0000 - accuracy: 0.9524 - precision: 0.9724 - recall: 0.9313 - auc: 0.9937 - 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\r",
      " 80/278 [=======>......................] - ETA: 4s - loss: 0.1057 - tp: 76367.0000 - fp: 2167.0000 - tn: 79672.0000 - fn: 5634.0000 - accuracy: 0.9524 - precision: 0.9724 - recall: 0.9313 - auc: 0.9937 - 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\r",
      " 83/278 [=======>......................] - ETA: 3s - loss: 0.1055 - tp: 79239.0000 - fp: 2236.0000 - tn: 82668.0000 - fn: 5841.0000 - accuracy: 0.9525 - precision: 0.9726 - recall: 0.9313 - auc: 0.9937 - 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\r",
      " 86/278 [========>.....................] - ETA: 3s - loss: 0.1053 - tp: 82124.0000 - fp: 2306.0000 - tn: 85647.0000 - fn: 6051.0000 - accuracy: 0.9526 - precision: 0.9727 - recall: 0.9314 - auc: 0.9937 - 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\r",
      " 89/278 [========>.....................] - ETA: 3s - loss: 0.1054 - tp: 85005.0000 - fp: 2399.0000 - tn: 88590.0000 - fn: 6278.0000 - accuracy: 0.9524 - precision: 0.9726 - recall: 0.9312 - auc: 0.9937 - 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\r",
      " 92/278 [========>.....................] - ETA: 3s - loss: 0.1052 - tp: 87881.0000 - fp: 2467.0000 - tn: 91592.0000 - fn: 6476.0000 - accuracy: 0.9525 - precision: 0.9727 - recall: 0.9314 - auc: 0.9938 - 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\b\r",
      " 95/278 [=========>....................] - ETA: 3s - loss: 0.1052 - tp: 90718.0000 - fp: 2552.0000 - tn: 94607.0000 - fn: 6683.0000 - accuracy: 0.9525 - precision: 0.9726 - recall: 0.9314 - auc: 0.9937 - 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\b\r",
      " 98/278 [=========>....................] - ETA: 3s - loss: 0.1053 - tp: 93540.0000 - fp: 2629.0000 - tn: 97637.0000 - fn: 6898.0000 - accuracy: 0.9525 - precision: 0.9727 - recall: 0.9313 - auc: 0.9937 - 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\b\r",
      "101/278 [=========>....................] - ETA: 3s - loss: 0.1054 - tp: 96391.0000 - fp: 2718.0000 - tn: 100634.0000 - fn: 7105.0000 - accuracy: 0.9525 - precision: 0.9726 - recall: 0.9313 - auc: 0.9937 - 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\r",
      "104/278 [==========>...................] - ETA: 3s - loss: 0.1053 - tp: 99257.0000 - fp: 2792.0000 - tn: 103617.0000 - fn: 7326.0000 - accuracy: 0.9525 - precision: 0.9726 - recall: 0.9313 - auc: 0.9937 - 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\r",
      "106/278 [==========>...................] - ETA: 3s - loss: 0.1055 - tp: 101185.0000 - fp: 2837.0000 - tn: 105589.0000 - fn: 7477.0000 - accuracy: 0.9525 - precision: 0.9727 - recall: 0.9312 - auc: 0.9937 - 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",
      "109/278 [==========>...................] - ETA: 3s - loss: 0.1052 - tp: 103999.0000 - fp: 2899.0000 - tn: 108655.0000 - fn: 7679.0000 - accuracy: 0.9526 - precision: 0.9729 - recall: 0.9312 - auc: 0.9938 - 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\b\b\b\r",
      "112/278 [===========>..................] - ETA: 3s - loss: 0.1052 - tp: 106861.0000 - fp: 2981.0000 - tn: 111636.0000 - fn: 7898.0000 - accuracy: 0.9526 - precision: 0.9729 - recall: 0.9312 - auc: 0.9938 - 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\b\b\b\r",
      "115/278 [===========>..................] - ETA: 3s - loss: 0.1052 - tp: 109702.0000 - fp: 3051.0000 - tn: 114643.0000 - fn: 8124.0000 - accuracy: 0.9526 - precision: 0.9729 - recall: 0.9311 - auc: 0.9938 - 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\b\b\b\r",
      "118/278 [===========>..................] - ETA: 3s - loss: 0.1051 - tp: 112483.0000 - fp: 3133.0000 - tn: 117709.0000 - fn: 8339.0000 - accuracy: 0.9525 - precision: 0.9729 - recall: 0.9310 - auc: 0.9938 - 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\b\b\b\r",
      "121/278 [============>.................] - ETA: 3s - loss: 0.1049 - tp: 115343.0000 - fp: 3207.0000 - tn: 120706.0000 - fn: 8552.0000 - accuracy: 0.9525 - precision: 0.9729 - recall: 0.9310 - auc: 0.9938 - 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\b\b\b\r",
      "124/278 [============>.................] - ETA: 3s - loss: 0.1049 - tp: 118196.0000 - fp: 3289.0000 - tn: 123701.0000 - fn: 8766.0000 - accuracy: 0.9525 - precision: 0.9729 - recall: 0.9310 - auc: 0.9938 - 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\b\b\b\r",
      "127/278 [============>.................] - ETA: 3s - loss: 0.1048 - tp: 121121.0000 - fp: 3365.0000 - tn: 126621.0000 - fn: 8989.0000 - accuracy: 0.9525 - precision: 0.9730 - recall: 0.9309 - auc: 0.9938 - 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\b\b\b\r",
      "130/278 [=============>................] - ETA: 3s - loss: 0.1047 - tp: 123995.0000 - fp: 3436.0000 - tn: 129595.0000 - fn: 9214.0000 - accuracy: 0.9525 - precision: 0.9730 - recall: 0.9308 - auc: 0.9938 - 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\b\b\b\r",
      "133/278 [=============>................] - ETA: 3s - loss: 0.1046 - tp: 126863.0000 - fp: 3521.0000 - tn: 132584.0000 - fn: 9416.0000 - accuracy: 0.9525 - precision: 0.9730 - recall: 0.9309 - auc: 0.9938 - 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\b\b\b\r",
      "136/278 [=============>................] - ETA: 2s - loss: 0.1046 - tp: 129689.0000 - fp: 3594.0000 - tn: 135636.0000 - fn: 9609.0000 - accuracy: 0.9526 - precision: 0.9730 - recall: 0.9310 - auc: 0.9939 - 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\b\b\b\r",
      "139/278 [==============>...............] - ETA: 2s - loss: 0.1046 - tp: 132544.0000 - fp: 3664.0000 - tn: 138642.0000 - fn: 9822.0000 - accuracy: 0.9526 - precision: 0.9731 - recall: 0.9310 - auc: 0.9939 - 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\b\b\b\r",
      "142/278 [==============>...............] - ETA: 2s - loss: 0.1045 - tp: 135276.0000 - fp: 3749.0000 - tn: 141770.0000 - fn: 10021.0000 - accuracy: 0.9527 - precision: 0.9730 - recall: 0.9310 - auc: 0.9939 - 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\b\b\b\b\r",
      "145/278 [==============>...............] - ETA: 2s - loss: 0.1044 - tp: 138126.0000 - fp: 3806.0000 - tn: 144806.0000 - fn: 10222.0000 - accuracy: 0.9528 - precision: 0.9732 - recall: 0.9311 - auc: 0.9939 - 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\b\b\b\b\r",
      "148/278 [==============>...............] - ETA: 2s - loss: 0.1043 - tp: 141028.0000 - fp: 3883.0000 - tn: 147768.0000 - fn: 10425.0000 - accuracy: 0.9528 - precision: 0.9732 - recall: 0.9312 - auc: 0.9939 - 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\b\b\b\b\r",
      "151/278 [===============>..............] - ETA: 2s - loss: 0.1042 - tp: 143916.0000 - fp: 3957.0000 - tn: 150735.0000 - fn: 10640.0000 - accuracy: 0.9528 - precision: 0.9732 - recall: 0.9312 - auc: 0.9939 - 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\b\b\b\b\r",
      "154/278 [===============>..............] - ETA: 2s - loss: 0.1041 - tp: 146843.0000 - fp: 4035.0000 - tn: 153676.0000 - fn: 10838.0000 - accuracy: 0.9528 - precision: 0.9733 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "157/278 [===============>..............] - ETA: 2s - loss: 0.1042 - tp: 149680.0000 - fp: 4122.0000 - tn: 156695.0000 - fn: 11039.0000 - accuracy: 0.9528 - precision: 0.9732 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "160/278 [================>.............] - ETA: 2s - loss: 0.1043 - tp: 152517.0000 - fp: 4188.0000 - tn: 159725.0000 - fn: 11250.0000 - accuracy: 0.9529 - precision: 0.9733 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "163/278 [================>.............] - ETA: 2s - loss: 0.1042 - tp: 155367.0000 - fp: 4256.0000 - tn: 162748.0000 - fn: 11453.0000 - accuracy: 0.9529 - precision: 0.9733 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "166/278 [================>.............] - ETA: 2s - loss: 0.1041 - tp: 158233.0000 - fp: 4340.0000 - tn: 165733.0000 - fn: 11662.0000 - accuracy: 0.9529 - precision: 0.9733 - recall: 0.9314 - auc: 0.9939 - 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\b\b\b\b\r",
      "169/278 [=================>............] - ETA: 2s - loss: 0.1041 - tp: 161118.0000 - fp: 4414.0000 - tn: 168701.0000 - fn: 11879.0000 - accuracy: 0.9529 - precision: 0.9733 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "172/278 [=================>............] - ETA: 2s - loss: 0.1040 - tp: 164011.0000 - fp: 4481.0000 - tn: 171667.0000 - fn: 12097.0000 - accuracy: 0.9529 - precision: 0.9734 - recall: 0.9313 - auc: 0.9939 - 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\b\b\b\b\r",
      "175/278 [=================>............] - ETA: 2s - loss: 0.1040 - tp: 166953.0000 - fp: 4555.0000 - tn: 174596.0000 - fn: 12296.0000 - accuracy: 0.9530 - precision: 0.9734 - recall: 0.9314 - auc: 0.9939 - 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\b\b\b\b\r",
      "178/278 [==================>...........] - ETA: 2s - loss: 0.1039 - tp: 169803.0000 - fp: 4622.0000 - tn: 177619.0000 - fn: 12500.0000 - accuracy: 0.9530 - precision: 0.9735 - recall: 0.9314 - auc: 0.9940 - 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\b\b\b\b\r",
      "181/278 [==================>...........] - ETA: 2s - loss: 0.1039 - tp: 172638.0000 - fp: 4701.0000 - tn: 180629.0000 - fn: 12720.0000 - accuracy: 0.9530 - precision: 0.9735 - recall: 0.9314 - auc: 0.9939 - 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\b\b\b\b\r",
      "184/278 [==================>...........] - ETA: 1s - loss: 0.1039 - tp: 175437.0000 - fp: 4777.0000 - tn: 183697.0000 - fn: 12921.0000 - accuracy: 0.9530 - precision: 0.9735 - recall: 0.9314 - auc: 0.9940 - 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\b\b\b\b\r",
      "187/278 [===================>..........] - ETA: 1s - loss: 0.1037 - tp: 178289.0000 - fp: 4842.0000 - tn: 186721.0000 - fn: 13124.0000 - accuracy: 0.9531 - precision: 0.9736 - recall: 0.9314 - auc: 0.9940 - 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\b\b\b\r",
      "190/278 [===================>..........] - ETA: 1s - loss: 0.1037 - tp: 181208.0000 - fp: 4922.0000 - tn: 189666.0000 - fn: 13324.0000 - accuracy: 0.9531 - precision: 0.9736 - recall: 0.9315 - auc: 0.9940 - 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\b\b\b\r",
      "193/278 [===================>..........] - ETA: 1s - loss: 0.1037 - tp: 184019.0000 - fp: 4985.0000 - tn: 192746.0000 - fn: 13514.0000 - accuracy: 0.9532 - precision: 0.9736 - recall: 0.9316 - auc: 0.9940 - 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\b\b\b\r",
      "196/278 [====================>.........] - ETA: 1s - loss: 0.1036 - tp: 186866.0000 - fp: 5058.0000 - tn: 195786.0000 - fn: 13698.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9317 - auc: 0.9940 - 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\b\b\b\r",
      "199/278 [====================>.........] - ETA: 1s - loss: 0.1035 - tp: 189749.0000 - fp: 5138.0000 - tn: 198763.0000 - fn: 13902.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9317 - auc: 0.9940 - 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\b\b\b\r",
      "202/278 [====================>.........] - ETA: 1s - loss: 0.1035 - tp: 192634.0000 - fp: 5204.0000 - tn: 201748.0000 - fn: 14110.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "204/278 [=====================>........] - ETA: 1s - loss: 0.1035 - tp: 194547.0000 - fp: 5263.0000 - tn: 203738.0000 - fn: 14244.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "207/278 [=====================>........] - ETA: 1s - loss: 0.1035 - tp: 197401.0000 - fp: 5345.0000 - tn: 206762.0000 - fn: 14428.0000 - accuracy: 0.9534 - precision: 0.9736 - recall: 0.9319 - auc: 0.9940 - 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\b\b\b\r",
      "210/278 [=====================>........] - ETA: 1s - loss: 0.1035 - tp: 200208.0000 - fp: 5426.0000 - tn: 209798.0000 - fn: 14648.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "213/278 [=====================>........] - ETA: 1s - loss: 0.1034 - tp: 203051.0000 - fp: 5491.0000 - tn: 212818.0000 - fn: 14864.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "216/278 [======================>.......] - ETA: 1s - loss: 0.1034 - tp: 205914.0000 - fp: 5577.0000 - tn: 215805.0000 - fn: 15072.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "219/278 [======================>.......] - ETA: 1s - loss: 0.1033 - tp: 208749.0000 - fp: 5648.0000 - tn: 218828.0000 - fn: 15287.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "222/278 [======================>.......] - ETA: 1s - loss: 0.1033 - tp: 211614.0000 - fp: 5726.0000 - tn: 221831.0000 - fn: 15485.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "225/278 [=======================>......] - ETA: 1s - loss: 0.1034 - tp: 214481.0000 - fp: 5809.0000 - tn: 224803.0000 - fn: 15707.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "228/278 [=======================>......] - ETA: 1s - loss: 0.1033 - tp: 217371.0000 - fp: 5888.0000 - tn: 227778.0000 - fn: 15907.0000 - accuracy: 0.9533 - precision: 0.9736 - recall: 0.9318 - auc: 0.9940 - 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\b\b\b\r",
      "231/278 [=======================>......] - ETA: 0s - loss: 0.1033 - tp: 220240.0000 - fp: 5948.0000 - tn: 230771.0000 - fn: 16129.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9318 - auc: 0.9941 - 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\b\b\b\r",
      "234/278 [========================>.....] - ETA: 0s - loss: 0.1032 - tp: 223144.0000 - fp: 6033.0000 - tn: 233737.0000 - fn: 16318.0000 - accuracy: 0.9534 - precision: 0.9737 - recall: 0.9319 - auc: 0.9941 - 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\b\b\b\r",
      "237/278 [========================>.....] - ETA: 0s - loss: 0.1031 - tp: 226061.0000 - fp: 6114.0000 - tn: 236677.0000 - fn: 16524.0000 - accuracy: 0.9534 - precision: 0.9737 - recall: 0.9319 - auc: 0.9941 - prc: 0.9940"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1032 - tp: 228965.0000 - fp: 6196.0000 - tn: 239617.0000 - fn: 16742.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9319 - auc: 0.9941 - 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\b\b\b\r",
      "243/278 [=========================>....] - ETA: 0s - loss: 0.1032 - tp: 231818.0000 - fp: 6271.0000 - tn: 242623.0000 - fn: 16952.0000 - accuracy: 0.9533 - precision: 0.9737 - recall: 0.9319 - auc: 0.9941 - 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\b\b\b\r",
      "246/278 [=========================>....] - ETA: 0s - loss: 0.1031 - tp: 234683.0000 - fp: 6333.0000 - tn: 245657.0000 - fn: 17135.0000 - accuracy: 0.9534 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "249/278 [=========================>....] - ETA: 0s - loss: 0.1031 - tp: 237491.0000 - fp: 6409.0000 - tn: 248719.0000 - fn: 17333.0000 - accuracy: 0.9534 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "252/278 [==========================>...] - ETA: 0s - loss: 0.1031 - tp: 240292.0000 - fp: 6484.0000 - tn: 251783.0000 - fn: 17537.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "255/278 [==========================>...] - ETA: 0s - loss: 0.1030 - tp: 243144.0000 - fp: 6559.0000 - tn: 254791.0000 - fn: 17746.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "258/278 [==========================>...] - ETA: 0s - loss: 0.1029 - tp: 246016.0000 - fp: 6635.0000 - tn: 257802.0000 - fn: 17931.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9321 - auc: 0.9941 - 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\b\b\b\r",
      "261/278 [===========================>..] - ETA: 0s - loss: 0.1029 - tp: 248864.0000 - fp: 6717.0000 - tn: 260789.0000 - fn: 18158.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "264/278 [===========================>..] - ETA: 0s - loss: 0.1029 - tp: 251645.0000 - fp: 6807.0000 - tn: 263854.0000 - fn: 18366.0000 - accuracy: 0.9534 - precision: 0.9737 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "267/278 [===========================>..] - ETA: 0s - loss: 0.1030 - tp: 254521.0000 - fp: 6893.0000 - tn: 266825.0000 - fn: 18577.0000 - accuracy: 0.9534 - precision: 0.9736 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "270/278 [============================>.] - ETA: 0s - loss: 0.1029 - tp: 257359.0000 - fp: 6977.0000 - tn: 269851.0000 - fn: 18773.0000 - accuracy: 0.9534 - precision: 0.9736 - recall: 0.9320 - auc: 0.9941 - 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\b\b\b\r",
      "273/278 [============================>.] - ETA: 0s - loss: 0.1029 - tp: 260230.0000 - fp: 7047.0000 - tn: 272862.0000 - fn: 18965.0000 - accuracy: 0.9535 - precision: 0.9736 - recall: 0.9321 - auc: 0.9941 - 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\b\b\b\r",
      "276/278 [============================>.] - ETA: 0s - loss: 0.1028 - tp: 263088.0000 - fp: 7116.0000 - tn: 275880.0000 - fn: 19164.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9321 - auc: 0.9941 - 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\b\b\b\r",
      "278/278 [==============================] - 6s 21ms/step - loss: 0.1028 - tp: 264967.0000 - fp: 7170.0000 - tn: 277903.0000 - fn: 19304.0000 - accuracy: 0.9535 - precision: 0.9737 - recall: 0.9321 - auc: 0.9941 - prc: 0.9940 - val_loss: 0.0468 - val_tp: 59.0000 - val_fp: 489.0000 - val_tn: 45011.0000 - val_fn: 10.0000 - val_accuracy: 0.9890 - val_precision: 0.1077 - val_recall: 0.8551 - val_auc: 0.9583 - val_prc: 0.6195\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.0992 - tp: 927.0000 - fp: 25.0000 - tn: 1021.0000 - fn: 75.0000 - accuracy: 0.9512 - precision: 0.9737 - recall: 0.9251 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0981 - tp: 4775.0000 - fp: 103.0000 - tn: 5014.0000 - fn: 348.0000 - accuracy: 0.9560 - precision: 0.9789 - recall: 0.9321 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1003 - tp: 7653.0000 - fp: 171.0000 - tn: 8001.0000 - fn: 559.0000 - accuracy: 0.9554 - precision: 0.9781 - recall: 0.9319 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0990 - tp: 10459.0000 - fp: 236.0000 - tn: 11059.0000 - fn: 774.0000 - accuracy: 0.9552 - precision: 0.9779 - recall: 0.9311 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 13331.0000 - fp: 305.0000 - tn: 14064.0000 - fn: 972.0000 - accuracy: 0.9555 - precision: 0.9776 - recall: 0.9320 - auc: 0.9950 - prc: 0.9949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0985 - tp: 16246.0000 - fp: 377.0000 - tn: 17016.0000 - fn: 1177.0000 - accuracy: 0.9554 - precision: 0.9773 - recall: 0.9324 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0981 - tp: 19090.0000 - fp: 448.0000 - tn: 20046.0000 - fn: 1376.0000 - accuracy: 0.9555 - precision: 0.9771 - recall: 0.9328 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0985 - tp: 21961.0000 - fp: 533.0000 - tn: 23028.0000 - fn: 1582.0000 - accuracy: 0.9551 - precision: 0.9763 - recall: 0.9328 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0984 - tp: 24871.0000 - fp: 607.0000 - tn: 25996.0000 - fn: 1774.0000 - accuracy: 0.9553 - precision: 0.9762 - recall: 0.9334 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0985 - tp: 27733.0000 - fp: 675.0000 - tn: 29004.0000 - fn: 1980.0000 - accuracy: 0.9553 - precision: 0.9762 - recall: 0.9334 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0982 - tp: 30576.0000 - fp: 744.0000 - tn: 32042.0000 - fn: 2174.0000 - accuracy: 0.9555 - precision: 0.9762 - recall: 0.9336 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0983 - tp: 33452.0000 - fp: 821.0000 - tn: 35017.0000 - fn: 2390.0000 - accuracy: 0.9552 - precision: 0.9760 - recall: 0.9333 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0979 - tp: 36311.0000 - fp: 894.0000 - tn: 38032.0000 - fn: 2587.0000 - accuracy: 0.9553 - precision: 0.9760 - recall: 0.9335 - auc: 0.9948 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0983 - tp: 39160.0000 - fp: 972.0000 - tn: 41057.0000 - fn: 2779.0000 - accuracy: 0.9553 - precision: 0.9758 - recall: 0.9337 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0985 - tp: 42043.0000 - fp: 1039.0000 - tn: 44061.0000 - fn: 2969.0000 - accuracy: 0.9555 - precision: 0.9759 - recall: 0.9340 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0986 - tp: 44940.0000 - fp: 1115.0000 - tn: 47045.0000 - fn: 3156.0000 - accuracy: 0.9556 - precision: 0.9758 - recall: 0.9344 - auc: 0.9948 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0987 - tp: 47851.0000 - fp: 1195.0000 - tn: 49988.0000 - fn: 3366.0000 - accuracy: 0.9555 - precision: 0.9756 - recall: 0.9343 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0987 - tp: 49769.0000 - fp: 1251.0000 - tn: 51971.0000 - fn: 3505.0000 - accuracy: 0.9553 - precision: 0.9755 - recall: 0.9342 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0986 - tp: 52686.0000 - fp: 1328.0000 - tn: 54928.0000 - fn: 3698.0000 - accuracy: 0.9554 - precision: 0.9754 - recall: 0.9344 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0986 - tp: 55549.0000 - fp: 1402.0000 - tn: 57934.0000 - fn: 3899.0000 - accuracy: 0.9554 - precision: 0.9754 - recall: 0.9344 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0985 - tp: 58411.0000 - fp: 1463.0000 - tn: 60947.0000 - fn: 4107.0000 - accuracy: 0.9554 - precision: 0.9756 - recall: 0.9343 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0986 - tp: 61326.0000 - fp: 1537.0000 - tn: 63898.0000 - fn: 4311.0000 - accuracy: 0.9554 - precision: 0.9755 - recall: 0.9343 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0986 - tp: 64207.0000 - fp: 1613.0000 - tn: 66881.0000 - fn: 4515.0000 - accuracy: 0.9553 - precision: 0.9755 - recall: 0.9343 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0984 - tp: 67096.0000 - fp: 1688.0000 - tn: 69860.0000 - fn: 4716.0000 - accuracy: 0.9553 - precision: 0.9755 - recall: 0.9343 - auc: 0.9947 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0984 - tp: 70018.0000 - fp: 1754.0000 - tn: 72813.0000 - fn: 4919.0000 - accuracy: 0.9554 - precision: 0.9756 - recall: 0.9344 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0983 - tp: 72866.0000 - fp: 1823.0000 - tn: 75826.0000 - fn: 5133.0000 - accuracy: 0.9553 - precision: 0.9756 - recall: 0.9342 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0982 - tp: 75716.0000 - fp: 1896.0000 - tn: 78848.0000 - fn: 5332.0000 - accuracy: 0.9553 - precision: 0.9756 - recall: 0.9342 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0982 - tp: 78603.0000 - fp: 1969.0000 - tn: 81815.0000 - fn: 5549.0000 - accuracy: 0.9552 - precision: 0.9756 - recall: 0.9341 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0982 - tp: 81465.0000 - fp: 2050.0000 - tn: 84827.0000 - fn: 5738.0000 - accuracy: 0.9553 - precision: 0.9755 - recall: 0.9342 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0982 - tp: 84354.0000 - fp: 2139.0000 - tn: 87814.0000 - fn: 5917.0000 - accuracy: 0.9553 - precision: 0.9753 - recall: 0.9345 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0982 - tp: 87272.0000 - fp: 2211.0000 - tn: 90779.0000 - fn: 6106.0000 - accuracy: 0.9554 - precision: 0.9753 - recall: 0.9346 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0980 - tp: 90080.0000 - fp: 2285.0000 - tn: 93855.0000 - fn: 6292.0000 - accuracy: 0.9554 - precision: 0.9753 - recall: 0.9347 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0980 - tp: 91969.0000 - fp: 2331.0000 - tn: 95883.0000 - fn: 6425.0000 - accuracy: 0.9555 - precision: 0.9753 - recall: 0.9347 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0980 - tp: 94881.0000 - fp: 2407.0000 - tn: 98846.0000 - fn: 6618.0000 - accuracy: 0.9555 - precision: 0.9753 - recall: 0.9348 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 97725.0000 - fp: 2481.0000 - tn: 101882.0000 - fn: 6808.0000 - accuracy: 0.9555 - precision: 0.9752 - recall: 0.9349 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 100606.0000 - fp: 2554.0000 - tn: 104868.0000 - fn: 7012.0000 - accuracy: 0.9555 - precision: 0.9752 - recall: 0.9348 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 103522.0000 - fp: 2622.0000 - tn: 107826.0000 - fn: 7214.0000 - accuracy: 0.9555 - precision: 0.9753 - recall: 0.9349 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 106374.0000 - fp: 2709.0000 - tn: 110826.0000 - fn: 7419.0000 - accuracy: 0.9554 - precision: 0.9752 - recall: 0.9348 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 109197.0000 - fp: 2779.0000 - tn: 113888.0000 - fn: 7608.0000 - accuracy: 0.9555 - precision: 0.9752 - recall: 0.9349 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 112057.0000 - fp: 2864.0000 - tn: 116886.0000 - fn: 7809.0000 - accuracy: 0.9555 - precision: 0.9751 - recall: 0.9349 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 114879.0000 - fp: 2936.0000 - tn: 119960.0000 - fn: 7985.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9350 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 117672.0000 - fp: 3013.0000 - tn: 123044.0000 - fn: 8175.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9350 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 120589.0000 - fp: 3078.0000 - tn: 126008.0000 - fn: 8373.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 123458.0000 - fp: 3152.0000 - tn: 129016.0000 - fn: 8566.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 126381.0000 - fp: 3231.0000 - tn: 131962.0000 - fn: 8762.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9352 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0979 - tp: 129268.0000 - fp: 3305.0000 - tn: 134941.0000 - fn: 8966.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0978 - tp: 132175.0000 - fp: 3371.0000 - tn: 137910.0000 - fn: 9168.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0979 - tp: 135032.0000 - fp: 3442.0000 - tn: 140917.0000 - fn: 9377.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0980 - tp: 137976.0000 - fp: 3524.0000 - tn: 143830.0000 - fn: 9582.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0980 - tp: 140823.0000 - fp: 3596.0000 - tn: 146862.0000 - fn: 9775.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 143689.0000 - fp: 3667.0000 - tn: 149877.0000 - fn: 9967.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "153/278 [===============>..............] - ETA: 2s - loss: 0.0979 - tp: 146541.0000 - fp: 3746.0000 - tn: 152890.0000 - fn: 10167.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 149468.0000 - fp: 3816.0000 - tn: 155833.0000 - fn: 10371.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0979 - tp: 152354.0000 - fp: 3904.0000 - tn: 158806.0000 - fn: 10568.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9351 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 155298.0000 - fp: 3988.0000 - tn: 161753.0000 - fn: 10737.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 158176.0000 - fp: 4069.0000 - tn: 164745.0000 - fn: 10930.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9354 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 161063.0000 - fp: 4124.0000 - tn: 167747.0000 - fn: 11130.0000 - accuracy: 0.9557 - precision: 0.9750 - recall: 0.9354 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0976 - tp: 163954.0000 - fp: 4193.0000 - tn: 170720.0000 - fn: 11341.0000 - accuracy: 0.9556 - precision: 0.9751 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 166799.0000 - fp: 4272.0000 - tn: 173740.0000 - fn: 11541.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 169717.0000 - fp: 4351.0000 - tn: 176694.0000 - fn: 11734.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0978 - tp: 172594.0000 - fp: 4432.0000 - tn: 179684.0000 - fn: 11930.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0978 - tp: 175472.0000 - fp: 4503.0000 - tn: 182665.0000 - fn: 12144.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0977 - tp: 178365.0000 - fp: 4583.0000 - tn: 185636.0000 - fn: 12344.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9353 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0977 - tp: 181180.0000 - fp: 4645.0000 - tn: 188688.0000 - fn: 12559.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9352 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0977 - tp: 184059.0000 - fp: 4727.0000 - tn: 191680.0000 - fn: 12750.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9352 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0976 - tp: 186870.0000 - fp: 4807.0000 - tn: 194736.0000 - fn: 12947.0000 - accuracy: 0.9555 - precision: 0.9749 - recall: 0.9352 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0975 - tp: 189873.0000 - fp: 4889.0000 - tn: 197616.0000 - fn: 13126.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9353 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0974 - tp: 192840.0000 - fp: 4954.0000 - tn: 200533.0000 - fn: 13321.0000 - accuracy: 0.9556 - precision: 0.9750 - recall: 0.9354 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0975 - tp: 195749.0000 - fp: 5039.0000 - tn: 203501.0000 - fn: 13503.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0976 - tp: 198566.0000 - fp: 5131.0000 - tn: 206525.0000 - fn: 13714.0000 - accuracy: 0.9555 - precision: 0.9748 - recall: 0.9354 - auc: 0.9948 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0975 - tp: 201422.0000 - fp: 5199.0000 - tn: 209560.0000 - fn: 13899.0000 - accuracy: 0.9556 - precision: 0.9748 - recall: 0.9354 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0974 - tp: 204354.0000 - fp: 5271.0000 - tn: 212514.0000 - fn: 14085.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0974 - tp: 207334.0000 - fp: 5351.0000 - tn: 215389.0000 - fn: 14294.0000 - accuracy: 0.9556 - precision: 0.9748 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0974 - tp: 210232.0000 - fp: 5432.0000 - tn: 218367.0000 - fn: 14481.0000 - accuracy: 0.9556 - precision: 0.9748 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0974 - tp: 213063.0000 - fp: 5497.0000 - tn: 221428.0000 - fn: 14668.0000 - accuracy: 0.9556 - precision: 0.9748 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0973 - tp: 215870.0000 - fp: 5565.0000 - tn: 224501.0000 - fn: 14864.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0972 - tp: 218740.0000 - fp: 5631.0000 - tn: 227485.0000 - fn: 15088.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.0973 - tp: 221613.0000 - fp: 5711.0000 - tn: 230485.0000 - fn: 15279.0000 - accuracy: 0.9556 - precision: 0.9749 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0972 - tp: 224445.0000 - fp: 5785.0000 - tn: 233545.0000 - fn: 15457.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0972 - tp: 227344.0000 - fp: 5867.0000 - tn: 236502.0000 - fn: 15663.0000 - accuracy: 0.9556 - precision: 0.9748 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0971 - tp: 230244.0000 - fp: 5930.0000 - tn: 239496.0000 - fn: 15850.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0971 - tp: 233117.0000 - fp: 5990.0000 - tn: 242506.0000 - fn: 16051.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9356 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0970 - tp: 236032.0000 - fp: 6057.0000 - tn: 245455.0000 - fn: 16264.0000 - accuracy: 0.9557 - precision: 0.9750 - recall: 0.9355 - auc: 0.9949 - prc: 0.9947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0970 - tp: 238928.0000 - fp: 6139.0000 - tn: 248433.0000 - fn: 16452.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9356 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0970 - tp: 241809.0000 - fp: 6223.0000 - tn: 251437.0000 - fn: 16627.0000 - accuracy: 0.9557 - precision: 0.9749 - recall: 0.9357 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0969 - tp: 244731.0000 - fp: 6315.0000 - tn: 254382.0000 - fn: 16812.0000 - accuracy: 0.9557 - precision: 0.9748 - recall: 0.9357 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0968 - tp: 247627.0000 - fp: 6373.0000 - tn: 257381.0000 - fn: 17003.0000 - accuracy: 0.9558 - precision: 0.9749 - recall: 0.9357 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0968 - tp: 250498.0000 - fp: 6447.0000 - tn: 260393.0000 - fn: 17190.0000 - accuracy: 0.9558 - precision: 0.9749 - recall: 0.9358 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 253382.0000 - fp: 6515.0000 - tn: 263416.0000 - fn: 17359.0000 - accuracy: 0.9558 - precision: 0.9749 - recall: 0.9359 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 256252.0000 - fp: 6595.0000 - tn: 266426.0000 - fn: 17543.0000 - accuracy: 0.9559 - precision: 0.9749 - recall: 0.9359 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 259172.0000 - fp: 6680.0000 - tn: 269374.0000 - fn: 17734.0000 - accuracy: 0.9558 - precision: 0.9749 - recall: 0.9360 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 261124.0000 - fp: 6729.0000 - tn: 271336.0000 - fn: 17867.0000 - accuracy: 0.9558 - precision: 0.9749 - recall: 0.9360 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 263011.0000 - fp: 6777.0000 - tn: 273370.0000 - fn: 17994.0000 - accuracy: 0.9559 - precision: 0.9749 - recall: 0.9360 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0967 - tp: 264922.0000 - fp: 6820.0000 - tn: 275380.0000 - fn: 18126.0000 - accuracy: 0.9559 - precision: 0.9749 - recall: 0.9360 - auc: 0.9949 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0966 - tp: 266834.0000 - fp: 6861.0000 - tn: 277391.0000 - fn: 18258.0000 - accuracy: 0.9559 - precision: 0.9749 - recall: 0.9360 - auc: 0.9950 - prc: 0.9948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 21ms/step - loss: 0.0966 - tp: 266834.0000 - fp: 6861.0000 - tn: 277391.0000 - fn: 18258.0000 - accuracy: 0.9559 - precision: 0.9749 - recall: 0.9360 - auc: 0.9950 - prc: 0.9948 - val_loss: 0.0435 - val_tp: 59.0000 - val_fp: 468.0000 - val_tn: 45032.0000 - val_fn: 10.0000 - val_accuracy: 0.9895 - val_precision: 0.1120 - val_recall: 0.8551 - val_auc: 0.9589 - val_prc: 0.6038\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.0873 - tp: 962.0000 - fp: 33.0000 - tn: 1001.0000 - fn: 52.0000 - accuracy: 0.9585 - precision: 0.9668 - recall: 0.9487 - auc: 0.9957 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0900 - tp: 4766.0000 - fp: 126.0000 - tn: 5050.0000 - fn: 298.0000 - accuracy: 0.9586 - precision: 0.9742 - recall: 0.9412 - auc: 0.9957 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0921 - tp: 7691.0000 - fp: 208.0000 - tn: 7993.0000 - fn: 492.0000 - accuracy: 0.9573 - precision: 0.9737 - recall: 0.9399 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0921 - tp: 10572.0000 - fp: 264.0000 - tn: 11008.0000 - fn: 684.0000 - accuracy: 0.9579 - precision: 0.9756 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0912 - tp: 13427.0000 - fp: 324.0000 - tn: 14055.0000 - fn: 866.0000 - accuracy: 0.9585 - precision: 0.9764 - recall: 0.9394 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0914 - tp: 16278.0000 - fp: 396.0000 - tn: 17079.0000 - fn: 1063.0000 - accuracy: 0.9581 - precision: 0.9763 - recall: 0.9387 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0909 - tp: 19183.0000 - fp: 464.0000 - tn: 20060.0000 - fn: 1253.0000 - accuracy: 0.9581 - precision: 0.9764 - recall: 0.9387 - auc: 0.9955 - prc: 0.9954"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0917 - tp: 22033.0000 - fp: 542.0000 - tn: 23073.0000 - fn: 1456.0000 - accuracy: 0.9576 - precision: 0.9760 - recall: 0.9380 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 24977.0000 - fp: 611.0000 - tn: 26023.0000 - fn: 1637.0000 - accuracy: 0.9578 - precision: 0.9761 - recall: 0.9385 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0915 - tp: 27875.0000 - fp: 674.0000 - tn: 29029.0000 - fn: 1814.0000 - accuracy: 0.9581 - precision: 0.9764 - recall: 0.9389 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0920 - tp: 30815.0000 - fp: 746.0000 - tn: 31974.0000 - fn: 2001.0000 - accuracy: 0.9581 - precision: 0.9764 - recall: 0.9390 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0917 - tp: 33702.0000 - fp: 811.0000 - tn: 34968.0000 - fn: 2199.0000 - accuracy: 0.9580 - precision: 0.9765 - recall: 0.9387 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0920 - tp: 36556.0000 - fp: 890.0000 - tn: 37990.0000 - fn: 2388.0000 - accuracy: 0.9579 - precision: 0.9762 - recall: 0.9387 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0923 - tp: 38440.0000 - fp: 951.0000 - tn: 40011.0000 - fn: 2518.0000 - accuracy: 0.9577 - precision: 0.9759 - recall: 0.9385 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0921 - tp: 41397.0000 - fp: 1002.0000 - tn: 42958.0000 - fn: 2707.0000 - accuracy: 0.9579 - precision: 0.9764 - recall: 0.9386 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0925 - tp: 44258.0000 - fp: 1093.0000 - tn: 45969.0000 - fn: 2888.0000 - accuracy: 0.9577 - precision: 0.9759 - recall: 0.9387 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0928 - tp: 47218.0000 - fp: 1162.0000 - tn: 48885.0000 - fn: 3087.0000 - accuracy: 0.9577 - precision: 0.9760 - recall: 0.9386 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0928 - tp: 50138.0000 - fp: 1227.0000 - tn: 51857.0000 - fn: 3274.0000 - accuracy: 0.9577 - precision: 0.9761 - recall: 0.9387 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0928 - tp: 53025.0000 - fp: 1302.0000 - tn: 54857.0000 - fn: 3456.0000 - accuracy: 0.9578 - precision: 0.9760 - recall: 0.9388 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0930 - tp: 55924.0000 - fp: 1394.0000 - tn: 57827.0000 - fn: 3639.0000 - accuracy: 0.9576 - precision: 0.9757 - recall: 0.9389 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0929 - tp: 58804.0000 - fp: 1487.0000 - tn: 60818.0000 - fn: 3819.0000 - accuracy: 0.9575 - precision: 0.9753 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0925 - tp: 61755.0000 - fp: 1544.0000 - tn: 63760.0000 - fn: 4013.0000 - accuracy: 0.9576 - precision: 0.9756 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 64709.0000 - fp: 1607.0000 - tn: 66693.0000 - fn: 4207.0000 - accuracy: 0.9576 - precision: 0.9758 - recall: 0.9390 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0922 - tp: 67536.0000 - fp: 1674.0000 - tn: 69760.0000 - fn: 4390.0000 - accuracy: 0.9577 - precision: 0.9758 - recall: 0.9390 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0920 - tp: 70438.0000 - fp: 1737.0000 - tn: 72742.0000 - fn: 4587.0000 - accuracy: 0.9577 - precision: 0.9759 - recall: 0.9389 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0920 - tp: 73267.0000 - fp: 1808.0000 - tn: 75797.0000 - fn: 4776.0000 - accuracy: 0.9577 - precision: 0.9759 - recall: 0.9388 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0919 - tp: 76149.0000 - fp: 1888.0000 - tn: 78798.0000 - fn: 4957.0000 - accuracy: 0.9577 - precision: 0.9758 - recall: 0.9389 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0919 - tp: 79066.0000 - fp: 1952.0000 - tn: 81792.0000 - fn: 5126.0000 - accuracy: 0.9579 - precision: 0.9759 - recall: 0.9391 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0919 - tp: 81947.0000 - fp: 2032.0000 - tn: 84796.0000 - fn: 5305.0000 - accuracy: 0.9579 - precision: 0.9758 - recall: 0.9392 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0918 - tp: 84873.0000 - fp: 2096.0000 - tn: 87761.0000 - fn: 5494.0000 - accuracy: 0.9579 - precision: 0.9759 - recall: 0.9392 - auc: 0.9955 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0920 - tp: 87740.0000 - fp: 2187.0000 - tn: 90750.0000 - fn: 5691.0000 - accuracy: 0.9577 - precision: 0.9757 - recall: 0.9391 - auc: 0.9954 - prc: 0.9953"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0923 - tp: 90647.0000 - fp: 2271.0000 - tn: 93709.0000 - fn: 5885.0000 - accuracy: 0.9576 - precision: 0.9756 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0923 - tp: 93511.0000 - fp: 2348.0000 - tn: 96734.0000 - fn: 6063.0000 - accuracy: 0.9577 - precision: 0.9755 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0923 - tp: 96391.0000 - fp: 2431.0000 - tn: 99725.0000 - fn: 6253.0000 - accuracy: 0.9576 - precision: 0.9754 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 98333.0000 - fp: 2481.0000 - tn: 101702.0000 - fn: 6380.0000 - accuracy: 0.9576 - precision: 0.9754 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 101258.0000 - fp: 2566.0000 - tn: 104651.0000 - fn: 6565.0000 - accuracy: 0.9575 - precision: 0.9753 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 104207.0000 - fp: 2632.0000 - tn: 107586.0000 - fn: 6759.0000 - accuracy: 0.9575 - precision: 0.9754 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0925 - tp: 107118.0000 - fp: 2705.0000 - tn: 110547.0000 - fn: 6958.0000 - accuracy: 0.9575 - precision: 0.9754 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 109992.0000 - fp: 2786.0000 - tn: 113552.0000 - fn: 7142.0000 - accuracy: 0.9575 - precision: 0.9753 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0925 - tp: 112865.0000 - fp: 2864.0000 - tn: 116555.0000 - fn: 7332.0000 - accuracy: 0.9574 - precision: 0.9753 - recall: 0.9390 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 115633.0000 - fp: 2936.0000 - tn: 119690.0000 - fn: 7501.0000 - accuracy: 0.9575 - precision: 0.9752 - recall: 0.9391 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0923 - tp: 118544.0000 - fp: 3000.0000 - tn: 122692.0000 - fn: 7668.0000 - accuracy: 0.9577 - precision: 0.9753 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 121422.0000 - fp: 3078.0000 - tn: 125690.0000 - fn: 7858.0000 - accuracy: 0.9576 - precision: 0.9753 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 123313.0000 - fp: 3128.0000 - tn: 127714.0000 - fn: 7989.0000 - accuracy: 0.9576 - precision: 0.9753 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 126189.0000 - fp: 3211.0000 - tn: 130720.0000 - fn: 8168.0000 - accuracy: 0.9576 - precision: 0.9752 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0923 - tp: 129044.0000 - fp: 3285.0000 - tn: 133762.0000 - fn: 8341.0000 - accuracy: 0.9576 - precision: 0.9752 - recall: 0.9393 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0924 - tp: 131923.0000 - fp: 3365.0000 - tn: 136759.0000 - fn: 8529.0000 - accuracy: 0.9576 - precision: 0.9751 - recall: 0.9393 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0923 - tp: 134760.0000 - fp: 3436.0000 - tn: 139819.0000 - fn: 8705.0000 - accuracy: 0.9577 - precision: 0.9751 - recall: 0.9393 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0924 - tp: 137580.0000 - fp: 3516.0000 - tn: 142870.0000 - fn: 8898.0000 - accuracy: 0.9576 - precision: 0.9751 - recall: 0.9393 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 140445.0000 - fp: 3596.0000 - tn: 145862.0000 - fn: 9105.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9391 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 143421.0000 - fp: 3681.0000 - tn: 148764.0000 - fn: 9286.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 146315.0000 - fp: 3746.0000 - tn: 151753.0000 - fn: 9482.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9391 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 149235.0000 - fp: 3836.0000 - tn: 154702.0000 - fn: 9667.0000 - accuracy: 0.9575 - precision: 0.9749 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 152177.0000 - fp: 3909.0000 - tn: 157658.0000 - fn: 9840.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9393 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 155063.0000 - fp: 3983.0000 - tn: 160656.0000 - fn: 10026.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9393 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 157950.0000 - fp: 4069.0000 - tn: 163626.0000 - fn: 10227.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 160846.0000 - fp: 4142.0000 - tn: 166614.0000 - fn: 10414.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 163720.0000 - fp: 4213.0000 - tn: 169632.0000 - fn: 10595.0000 - accuracy: 0.9575 - precision: 0.9749 - recall: 0.9392 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 166595.0000 - fp: 4281.0000 - tn: 172633.0000 - fn: 10795.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9391 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 169421.0000 - fp: 4364.0000 - tn: 175674.0000 - fn: 10989.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9391 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0927 - tp: 172285.0000 - fp: 4441.0000 - tn: 178681.0000 - fn: 11185.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0926 - tp: 175149.0000 - fp: 4506.0000 - tn: 181702.0000 - fn: 11379.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0926 - tp: 178034.0000 - fp: 4574.0000 - tn: 184714.0000 - fn: 11558.0000 - accuracy: 0.9574 - precision: 0.9750 - recall: 0.9390 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0926 - tp: 180919.0000 - fp: 4663.0000 - tn: 187692.0000 - fn: 11750.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9953 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0925 - tp: 183787.0000 - fp: 4724.0000 - tn: 190721.0000 - fn: 11936.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 186666.0000 - fp: 4785.0000 - tn: 193739.0000 - fn: 12122.0000 - accuracy: 0.9574 - precision: 0.9750 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 189491.0000 - fp: 4854.0000 - tn: 196801.0000 - fn: 12310.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 192379.0000 - fp: 4943.0000 - tn: 199776.0000 - fn: 12502.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 195297.0000 - fp: 5030.0000 - tn: 202736.0000 - fn: 12681.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 198204.0000 - fp: 5095.0000 - tn: 205743.0000 - fn: 12846.0000 - accuracy: 0.9575 - precision: 0.9749 - recall: 0.9391 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 201048.0000 - fp: 5165.0000 - tn: 208779.0000 - fn: 13040.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9391 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 203905.0000 - fp: 5241.0000 - tn: 211793.0000 - fn: 13237.0000 - accuracy: 0.9574 - precision: 0.9749 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 206808.0000 - fp: 5307.0000 - tn: 214778.0000 - fn: 13427.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9390 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 209696.0000 - fp: 5373.0000 - tn: 217794.0000 - fn: 13601.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9391 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0924 - tp: 212591.0000 - fp: 5440.0000 - tn: 220800.0000 - fn: 13777.0000 - accuracy: 0.9575 - precision: 0.9750 - recall: 0.9391 - auc: 0.9954 - prc: 0.9951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0922 - tp: 215485.0000 - fp: 5507.0000 - tn: 223801.0000 - fn: 13959.0000 - accuracy: 0.9576 - precision: 0.9751 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0923 - tp: 218448.0000 - fp: 5592.0000 - tn: 226715.0000 - fn: 14141.0000 - accuracy: 0.9576 - precision: 0.9750 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0922 - tp: 221306.0000 - fp: 5652.0000 - tn: 229760.0000 - fn: 14322.0000 - accuracy: 0.9576 - precision: 0.9751 - recall: 0.9392 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0s - loss: 0.0921 - tp: 224217.0000 - fp: 5738.0000 - tn: 232742.0000 - fn: 14487.0000 - accuracy: 0.9576 - precision: 0.9750 - recall: 0.9393 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0920 - tp: 227101.0000 - fp: 5805.0000 - tn: 235771.0000 - fn: 14651.0000 - accuracy: 0.9577 - precision: 0.9751 - recall: 0.9394 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0920 - tp: 229933.0000 - fp: 5889.0000 - tn: 238827.0000 - fn: 14823.0000 - accuracy: 0.9577 - precision: 0.9750 - recall: 0.9394 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0919 - tp: 232782.0000 - fp: 5946.0000 - tn: 241899.0000 - fn: 14989.0000 - accuracy: 0.9578 - precision: 0.9751 - recall: 0.9395 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0918 - tp: 235629.0000 - fp: 6008.0000 - tn: 244954.0000 - fn: 15169.0000 - accuracy: 0.9578 - precision: 0.9751 - recall: 0.9395 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0918 - tp: 238459.0000 - fp: 6092.0000 - tn: 248020.0000 - fn: 15333.0000 - accuracy: 0.9578 - precision: 0.9751 - recall: 0.9396 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0918 - tp: 241445.0000 - fp: 6165.0000 - tn: 250921.0000 - fn: 15517.0000 - accuracy: 0.9578 - precision: 0.9751 - recall: 0.9396 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0917 - tp: 244345.0000 - fp: 6237.0000 - tn: 253905.0000 - fn: 15705.0000 - accuracy: 0.9578 - precision: 0.9751 - recall: 0.9396 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0917 - tp: 246273.0000 - fp: 6278.0000 - tn: 255919.0000 - fn: 15818.0000 - accuracy: 0.9579 - precision: 0.9751 - recall: 0.9396 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0917 - tp: 249124.0000 - fp: 6347.0000 - tn: 258958.0000 - fn: 16003.0000 - accuracy: 0.9579 - precision: 0.9752 - recall: 0.9396 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0917 - tp: 252019.0000 - fp: 6425.0000 - tn: 261961.0000 - fn: 16171.0000 - accuracy: 0.9579 - precision: 0.9751 - recall: 0.9397 - auc: 0.9954 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 254931.0000 - fp: 6486.0000 - tn: 264968.0000 - fn: 16335.0000 - accuracy: 0.9580 - precision: 0.9752 - recall: 0.9398 - auc: 0.9955 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 257805.0000 - fp: 6568.0000 - tn: 267989.0000 - fn: 16502.0000 - accuracy: 0.9580 - precision: 0.9752 - recall: 0.9398 - auc: 0.9955 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 260676.0000 - fp: 6639.0000 - tn: 270992.0000 - fn: 16701.0000 - accuracy: 0.9579 - precision: 0.9752 - recall: 0.9398 - auc: 0.9955 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 263514.0000 - fp: 6700.0000 - tn: 274059.0000 - fn: 16879.0000 - accuracy: 0.9580 - precision: 0.9752 - recall: 0.9398 - auc: 0.9955 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0916 - tp: 265455.0000 - fp: 6748.0000 - tn: 276047.0000 - fn: 16998.0000 - accuracy: 0.9580 - precision: 0.9752 - recall: 0.9398 - auc: 0.9955 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 21ms/step - loss: 0.0916 - tp: 267421.0000 - fp: 6806.0000 - tn: 278008.0000 - fn: 17109.0000 - accuracy: 0.9580 - precision: 0.9752 - recall: 0.9399 - auc: 0.9955 - prc: 0.9952 - val_loss: 0.0396 - val_tp: 60.0000 - val_fp: 428.0000 - val_tn: 45072.0000 - val_fn: 9.0000 - val_accuracy: 0.9904 - val_precision: 0.1230 - val_recall: 0.8696 - val_auc: 0.9548 - val_prc: 0.6051\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/278 [..............................] - ETA: 1s - loss: 0.0961 - tp: 969.0000 - fp: 21.0000 - tn: 1005.0000 - fn: 53.0000 - accuracy: 0.9639 - precision: 0.9788 - recall: 0.9481 - auc: 0.9952 - 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\r",
      "  4/278 [..............................] - ETA: 4s - loss: 0.0987 - tp: 3816.0000 - fp: 104.0000 - tn: 4040.0000 - fn: 232.0000 - accuracy: 0.9590 - precision: 0.9735 - recall: 0.9427 - auc: 0.9949 - 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\r",
      "  7/278 [..............................] - ETA: 5s - loss: 0.0926 - tp: 6664.0000 - fp: 164.0000 - tn: 7106.0000 - fn: 402.0000 - accuracy: 0.9605 - precision: 0.9760 - recall: 0.9431 - auc: 0.9955 - prc: 0.9949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0910 - tp: 9554.0000 - fp: 247.0000 - tn: 10098.0000 - fn: 581.0000 - accuracy: 0.9596 - precision: 0.9748 - recall: 0.9427 - auc: 0.9956 - prc: 0.9952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0901 - tp: 12488.0000 - fp: 311.0000 - tn: 13073.0000 - fn: 752.0000 - accuracy: 0.9601 - precision: 0.9757 - recall: 0.9432 - auc: 0.9958 - prc: 0.9954"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 15438.0000 - fp: 373.0000 - tn: 16019.0000 - fn: 938.0000 - accuracy: 0.9600 - precision: 0.9764 - recall: 0.9427 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 18310.0000 - fp: 423.0000 - tn: 19061.0000 - fn: 1118.0000 - accuracy: 0.9604 - precision: 0.9774 - recall: 0.9425 - auc: 0.9960 - prc: 0.9958"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0888 - tp: 21257.0000 - fp: 501.0000 - tn: 22001.0000 - fn: 1297.0000 - accuracy: 0.9601 - precision: 0.9770 - recall: 0.9425 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 24171.0000 - fp: 577.0000 - tn: 24983.0000 - fn: 1469.0000 - accuracy: 0.9600 - precision: 0.9767 - recall: 0.9427 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0883 - tp: 27072.0000 - fp: 657.0000 - tn: 27981.0000 - fn: 1634.0000 - accuracy: 0.9600 - precision: 0.9763 - recall: 0.9431 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0883 - tp: 29945.0000 - fp: 743.0000 - tn: 30992.0000 - fn: 1808.0000 - accuracy: 0.9598 - precision: 0.9758 - recall: 0.9431 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0880 - tp: 32824.0000 - fp: 823.0000 - tn: 34003.0000 - fn: 1982.0000 - accuracy: 0.9597 - precision: 0.9755 - recall: 0.9431 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0878 - tp: 35702.0000 - fp: 893.0000 - tn: 37026.0000 - fn: 2155.0000 - accuracy: 0.9598 - precision: 0.9756 - recall: 0.9431 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4s - loss: 0.0879 - tp: 38581.0000 - fp: 968.0000 - tn: 40021.0000 - fn: 2350.0000 - accuracy: 0.9595 - precision: 0.9755 - recall: 0.9426 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0877 - tp: 41504.0000 - fp: 1041.0000 - tn: 42990.0000 - fn: 2529.0000 - accuracy: 0.9595 - precision: 0.9755 - recall: 0.9426 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0877 - tp: 44402.0000 - fp: 1106.0000 - tn: 46003.0000 - fn: 2697.0000 - accuracy: 0.9596 - precision: 0.9757 - recall: 0.9427 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0878 - tp: 47350.0000 - fp: 1182.0000 - tn: 48950.0000 - fn: 2870.0000 - accuracy: 0.9596 - precision: 0.9756 - recall: 0.9429 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 50226.0000 - fp: 1261.0000 - tn: 51957.0000 - fn: 3052.0000 - accuracy: 0.9595 - precision: 0.9755 - recall: 0.9427 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0883 - tp: 53124.0000 - fp: 1346.0000 - tn: 54942.0000 - fn: 3228.0000 - accuracy: 0.9594 - precision: 0.9753 - recall: 0.9427 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 56038.0000 - fp: 1426.0000 - tn: 57927.0000 - fn: 3393.0000 - accuracy: 0.9594 - precision: 0.9752 - recall: 0.9429 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0882 - tp: 57964.0000 - fp: 1485.0000 - tn: 59927.0000 - fn: 3504.0000 - accuracy: 0.9594 - precision: 0.9750 - recall: 0.9430 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 60897.0000 - fp: 1561.0000 - tn: 62894.0000 - fn: 3672.0000 - accuracy: 0.9594 - precision: 0.9750 - recall: 0.9431 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0890 - tp: 63799.0000 - fp: 1645.0000 - tn: 65854.0000 - fn: 3870.0000 - accuracy: 0.9592 - precision: 0.9749 - recall: 0.9428 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0891 - tp: 66691.0000 - fp: 1718.0000 - tn: 68849.0000 - fn: 4054.0000 - accuracy: 0.9592 - precision: 0.9749 - recall: 0.9427 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0891 - tp: 69581.0000 - fp: 1792.0000 - tn: 71835.0000 - fn: 4248.0000 - accuracy: 0.9590 - precision: 0.9749 - recall: 0.9425 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0890 - tp: 72458.0000 - fp: 1870.0000 - tn: 74847.0000 - fn: 4425.0000 - accuracy: 0.9590 - precision: 0.9748 - recall: 0.9424 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0888 - tp: 75421.0000 - fp: 1939.0000 - tn: 77790.0000 - fn: 4594.0000 - accuracy: 0.9591 - precision: 0.9749 - recall: 0.9426 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0887 - tp: 78406.0000 - fp: 2014.0000 - tn: 80694.0000 - fn: 4774.0000 - accuracy: 0.9591 - precision: 0.9750 - recall: 0.9426 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0891 - tp: 81288.0000 - fp: 2102.0000 - tn: 83692.0000 - fn: 4950.0000 - accuracy: 0.9590 - precision: 0.9748 - recall: 0.9426 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0889 - tp: 84196.0000 - fp: 2178.0000 - tn: 86694.0000 - fn: 5108.0000 - accuracy: 0.9591 - precision: 0.9748 - recall: 0.9428 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0892 - tp: 87048.0000 - fp: 2257.0000 - tn: 89725.0000 - fn: 5290.0000 - accuracy: 0.9591 - precision: 0.9747 - recall: 0.9427 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0892 - tp: 89910.0000 - fp: 2333.0000 - tn: 92732.0000 - fn: 5489.0000 - accuracy: 0.9589 - precision: 0.9747 - recall: 0.9425 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0890 - tp: 92773.0000 - fp: 2401.0000 - tn: 95775.0000 - fn: 5659.0000 - accuracy: 0.9590 - precision: 0.9748 - recall: 0.9425 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 3s - loss: 0.0888 - tp: 95678.0000 - fp: 2468.0000 - tn: 98774.0000 - fn: 5832.0000 - accuracy: 0.9591 - precision: 0.9749 - recall: 0.9425 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0887 - tp: 98583.0000 - fp: 2538.0000 - tn: 101756.0000 - fn: 6019.0000 - accuracy: 0.9590 - precision: 0.9749 - recall: 0.9425 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0887 - tp: 101455.0000 - fp: 2612.0000 - tn: 104766.0000 - fn: 6207.0000 - accuracy: 0.9590 - precision: 0.9749 - recall: 0.9423 - auc: 0.9957 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 104378.0000 - fp: 2674.0000 - tn: 107754.0000 - fn: 6378.0000 - accuracy: 0.9591 - precision: 0.9750 - recall: 0.9424 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 106305.0000 - fp: 2731.0000 - tn: 109756.0000 - fn: 6488.0000 - accuracy: 0.9591 - precision: 0.9750 - recall: 0.9425 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0887 - tp: 109205.0000 - fp: 2806.0000 - tn: 112759.0000 - fn: 6654.0000 - accuracy: 0.9591 - precision: 0.9749 - recall: 0.9426 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 112058.0000 - fp: 2870.0000 - tn: 115834.0000 - fn: 6806.0000 - accuracy: 0.9593 - precision: 0.9750 - recall: 0.9427 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 114991.0000 - fp: 2936.0000 - tn: 118805.0000 - fn: 6980.0000 - accuracy: 0.9593 - precision: 0.9751 - recall: 0.9428 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 117937.0000 - fp: 3003.0000 - tn: 121763.0000 - fn: 7153.0000 - accuracy: 0.9594 - precision: 0.9752 - recall: 0.9428 - auc: 0.9958 - prc: 0.9955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 120867.0000 - fp: 3074.0000 - tn: 124724.0000 - fn: 7335.0000 - accuracy: 0.9593 - precision: 0.9752 - recall: 0.9428 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0886 - tp: 123786.0000 - fp: 3160.0000 - tn: 127694.0000 - fn: 7504.0000 - accuracy: 0.9593 - precision: 0.9751 - recall: 0.9428 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 126643.0000 - fp: 3222.0000 - tn: 130746.0000 - fn: 7677.0000 - accuracy: 0.9594 - precision: 0.9752 - recall: 0.9428 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 129561.0000 - fp: 3288.0000 - tn: 133734.0000 - fn: 7849.0000 - accuracy: 0.9594 - precision: 0.9753 - recall: 0.9429 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0885 - tp: 132549.0000 - fp: 3353.0000 - tn: 136659.0000 - fn: 8015.0000 - accuracy: 0.9595 - precision: 0.9753 - recall: 0.9430 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0884 - tp: 135394.0000 - fp: 3427.0000 - tn: 139717.0000 - fn: 8182.0000 - accuracy: 0.9595 - precision: 0.9753 - recall: 0.9430 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 2s - loss: 0.0883 - tp: 138285.0000 - fp: 3508.0000 - tn: 142724.0000 - fn: 8347.0000 - accuracy: 0.9595 - precision: 0.9753 - recall: 0.9431 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 141208.0000 - fp: 3569.0000 - tn: 145725.0000 - fn: 8506.0000 - accuracy: 0.9596 - precision: 0.9753 - recall: 0.9432 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 144087.0000 - fp: 3640.0000 - tn: 148752.0000 - fn: 8673.0000 - accuracy: 0.9596 - precision: 0.9754 - recall: 0.9432 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 146965.0000 - fp: 3711.0000 - tn: 151787.0000 - fn: 8833.0000 - accuracy: 0.9597 - precision: 0.9754 - recall: 0.9433 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0880 - tp: 149830.0000 - fp: 3793.0000 - tn: 154814.0000 - fn: 9003.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9433 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0881 - tp: 152772.0000 - fp: 3873.0000 - tn: 157765.0000 - fn: 9174.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9434 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0880 - tp: 155653.0000 - fp: 3946.0000 - tn: 160791.0000 - fn: 9338.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9434 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0879 - tp: 157601.0000 - fp: 3996.0000 - tn: 162779.0000 - fn: 9448.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9434 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0880 - tp: 159574.0000 - fp: 4053.0000 - tn: 164733.0000 - fn: 9560.0000 - accuracy: 0.9597 - precision: 0.9752 - recall: 0.9435 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0879 - tp: 162528.0000 - fp: 4122.0000 - tn: 167682.0000 - fn: 9732.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9435 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0879 - tp: 165400.0000 - fp: 4197.0000 - tn: 170709.0000 - fn: 9902.0000 - accuracy: 0.9597 - precision: 0.9753 - recall: 0.9435 - auc: 0.9958 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0878 - tp: 168350.0000 - fp: 4262.0000 - tn: 173687.0000 - fn: 10053.0000 - accuracy: 0.9598 - precision: 0.9753 - recall: 0.9437 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0878 - tp: 171274.0000 - fp: 4342.0000 - tn: 176664.0000 - fn: 10216.0000 - accuracy: 0.9598 - precision: 0.9753 - recall: 0.9437 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0877 - tp: 174190.0000 - fp: 4407.0000 - tn: 179677.0000 - fn: 10366.0000 - accuracy: 0.9599 - precision: 0.9753 - recall: 0.9438 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0876 - tp: 177091.0000 - fp: 4475.0000 - tn: 182693.0000 - fn: 10525.0000 - accuracy: 0.9600 - precision: 0.9754 - recall: 0.9439 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0877 - tp: 180027.0000 - fp: 4554.0000 - tn: 185645.0000 - fn: 10702.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9439 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1s - loss: 0.0876 - tp: 182953.0000 - fp: 4619.0000 - tn: 188636.0000 - fn: 10864.0000 - accuracy: 0.9600 - precision: 0.9754 - recall: 0.9439 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 185876.0000 - fp: 4694.0000 - tn: 191601.0000 - fn: 11045.0000 - accuracy: 0.9600 - precision: 0.9754 - recall: 0.9439 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 188806.0000 - fp: 4764.0000 - tn: 194583.0000 - fn: 11207.0000 - accuracy: 0.9600 - precision: 0.9754 - recall: 0.9440 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 191754.0000 - fp: 4845.0000 - tn: 197549.0000 - fn: 11356.0000 - accuracy: 0.9600 - precision: 0.9754 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0876 - tp: 194647.0000 - fp: 4928.0000 - tn: 200548.0000 - fn: 11525.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0876 - tp: 196535.0000 - fp: 4979.0000 - tn: 202594.0000 - fn: 11636.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0876 - tp: 199469.0000 - fp: 5067.0000 - tn: 205558.0000 - fn: 11794.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9442 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 202348.0000 - fp: 5131.0000 - tn: 208581.0000 - fn: 11972.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0874 - tp: 205265.0000 - fp: 5201.0000 - tn: 211564.0000 - fn: 12146.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0875 - tp: 208162.0000 - fp: 5274.0000 - tn: 214559.0000 - fn: 12325.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0874 - tp: 211026.0000 - fp: 5346.0000 - tn: 217600.0000 - fn: 12492.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0874 - tp: 213909.0000 - fp: 5426.0000 - tn: 220600.0000 - fn: 12673.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 216796.0000 - fp: 5500.0000 - tn: 223617.0000 - fn: 12839.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 219708.0000 - fp: 5571.0000 - tn: 226602.0000 - fn: 13015.0000 - accuracy: 0.9600 - precision: 0.9753 - recall: 0.9441 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 222663.0000 - fp: 5662.0000 - tn: 229539.0000 - fn: 13176.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0874 - tp: 224592.0000 - fp: 5724.0000 - tn: 231534.0000 - fn: 13286.0000 - accuracy: 0.9600 - precision: 0.9751 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 227478.0000 - fp: 5789.0000 - tn: 234572.0000 - fn: 13441.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9442 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 230338.0000 - fp: 5856.0000 - tn: 237609.0000 - fn: 13621.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9442 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 233237.0000 - fp: 5941.0000 - tn: 240602.0000 - fn: 13788.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9442 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0873 - tp: 236134.0000 - fp: 6015.0000 - tn: 243593.0000 - fn: 13970.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0872 - tp: 239023.0000 - fp: 6067.0000 - tn: 246617.0000 - fn: 14149.0000 - accuracy: 0.9600 - precision: 0.9752 - recall: 0.9441 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0872 - tp: 241969.0000 - fp: 6134.0000 - tn: 249604.0000 - fn: 14293.0000 - accuracy: 0.9601 - precision: 0.9753 - recall: 0.9442 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0872 - tp: 244849.0000 - fp: 6207.0000 - tn: 252614.0000 - fn: 14474.0000 - accuracy: 0.9601 - precision: 0.9753 - recall: 0.9442 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0871 - tp: 247781.0000 - fp: 6277.0000 - tn: 255607.0000 - fn: 14623.0000 - accuracy: 0.9601 - precision: 0.9753 - recall: 0.9443 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0871 - tp: 250695.0000 - fp: 6359.0000 - tn: 258596.0000 - fn: 14782.0000 - accuracy: 0.9601 - precision: 0.9753 - recall: 0.9443 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0871 - tp: 253552.0000 - fp: 6446.0000 - tn: 261645.0000 - fn: 14933.0000 - accuracy: 0.9602 - precision: 0.9752 - recall: 0.9444 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0871 - tp: 256481.0000 - fp: 6524.0000 - tn: 264599.0000 - fn: 15116.0000 - accuracy: 0.9601 - precision: 0.9752 - recall: 0.9443 - auc: 0.9959 - prc: 0.9956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0870 - tp: 259429.0000 - fp: 6582.0000 - tn: 267570.0000 - fn: 15283.0000 - accuracy: 0.9602 - precision: 0.9753 - recall: 0.9444 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0870 - tp: 262353.0000 - fp: 6660.0000 - tn: 270542.0000 - fn: 15453.0000 - accuracy: 0.9602 - precision: 0.9752 - recall: 0.9444 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0870 - tp: 265274.0000 - fp: 6717.0000 - tn: 273533.0000 - fn: 15628.0000 - accuracy: 0.9602 - precision: 0.9753 - recall: 0.9444 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0870 - tp: 268244.0000 - fp: 6786.0000 - tn: 276469.0000 - fn: 15797.0000 - accuracy: 0.9602 - precision: 0.9753 - recall: 0.9444 - auc: 0.9959 - prc: 0.9957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 1.\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: 0.0870 - tp: 269189.0000 - fp: 6815.0000 - tn: 277494.0000 - fn: 15846.0000 - accuracy: 0.9602 - precision: 0.9753 - recall: 0.9444 - auc: 0.9959 - prc: 0.9957 - val_loss: 0.0365 - val_tp: 60.0000 - val_fp: 401.0000 - val_tn: 45099.0000 - val_fn: 9.0000 - val_accuracy: 0.9910 - val_precision: 0.1302 - val_recall: 0.8696 - val_auc: 0.9509 - val_prc: 0.6138\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11: 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": [
    "トレーニングプロセスが勾配の更新ごとにデータセット全体を考慮する場合は、このオーバーサンプリングは基本的にクラスの重み付けと同じになります。\n",
    "\n",
    "しかし、ここで行ったようにバッチ単位でモデルをトレーニングする場合、オーバーサンプリングされたデータはより滑らかな勾配信号を提供します。それぞれの陽性の例を大きな重みを持つ 1 つのバッチで表示する代わりに、毎回小さな重みを持つ多くの異なるバッチで表示します。\n",
    "\n",
    "このような滑らかな勾配信号は、モデルのトレーニングを容易にします。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "klHZ0HV76VC5"
   },
   "source": [
    "### トレーニング履歴を確認する\n",
    "\n",
    "トレーニングデータは検証データやテストデータとは全く異なる分散を持つため、ここでのメトリクスの分散は異なることに注意してください。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:02.968929Z",
     "iopub.status.busy": "2022-12-14T23:08:02.968321Z",
     "iopub.status.idle": "2022-12-14T23:08:03.574622Z",
     "shell.execute_reply": "2022-12-14T23:08:03.573887Z"
    },
    "id": "YoUGfr1vuivl"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### 再トレーニングする\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KFLxRL8eoDE5"
   },
   "source": [
    "バランスの取れたデータの方がトレーニングしやすいため、上記のトレーニング方法ではすぐに過学習してしまう可能性があります。\n",
    "\n",
    "したがって、エポックを分割して、`tf.keras.callbacks.EarlyStopping` がトレーニングを停止するタイミングをより細かく制御できるようにします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:03.579890Z",
     "iopub.status.busy": "2022-12-14T23:08:03.579037Z",
     "iopub.status.idle": "2022-12-14T23:08:21.136535Z",
     "shell.execute_reply": "2022-12-14T23:08:21.135792Z"
    },
    "id": "e_yn9I26qAHU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 30s - loss: 1.4319 - tp: 416.0000 - fp: 612.0000 - tn: 45893.0000 - fn: 696.0000 - accuracy: 0.9725 - precision: 0.4047 - recall: 0.3741 - auc: 0.8803 - prc: 0.3647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.3621 - tp: 2002.0000 - fp: 1669.0000 - tn: 48902.0000 - fn: 3236.0000 - accuracy: 0.9121 - precision: 0.5454 - recall: 0.3822 - auc: 0.8511 - prc: 0.4999"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.3069 - tp: 2887.0000 - fp: 2186.0000 - tn: 50432.0000 - fn: 4400.0000 - accuracy: 0.8901 - precision: 0.5691 - recall: 0.3962 - auc: 0.8442 - prc: 0.5384"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.2410 - tp: 4295.0000 - fp: 2952.0000 - tn: 52719.0000 - fn: 6083.0000 - accuracy: 0.8632 - precision: 0.5927 - recall: 0.4139 - auc: 0.8363 - 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\b\b\b\b\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 1.1807 - tp: 5850.0000 - fp: 3771.0000 - tn: 54997.0000 - fn: 7575.0000 - accuracy: 0.8428 - precision: 0.6080 - recall: 0.4358 - auc: 0.8297 - prc: 0.6077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.1336 - tp: 7512.0000 - fp: 4587.0000 - tn: 57230.0000 - fn: 9008.0000 - accuracy: 0.8265 - precision: 0.6209 - recall: 0.4547 - auc: 0.8241 - prc: 0.6311"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 1.0918 - tp: 9285.0000 - fp: 5420.0000 - tn: 59426.0000 - fn: 10350.0000 - accuracy: 0.8133 - precision: 0.6314 - recall: 0.4729 - auc: 0.8200 - prc: 0.6523"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 54ms/step - loss: 1.0788 - tp: 9883.0000 - fp: 5709.0000 - tn: 60165.0000 - fn: 10772.0000 - accuracy: 0.8095 - precision: 0.6339 - recall: 0.4785 - auc: 0.8187 - prc: 0.6587 - val_loss: 0.4735 - val_tp: 44.0000 - val_fp: 7517.0000 - val_tn: 37983.0000 - val_fn: 25.0000 - val_accuracy: 0.8345 - val_precision: 0.0058 - val_recall: 0.6377 - val_auc: 0.7719 - val_prc: 0.1136\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.8351 - tp: 612.0000 - fp: 280.0000 - tn: 734.0000 - fn: 422.0000 - accuracy: 0.6572 - precision: 0.6861 - recall: 0.5919 - auc: 0.6684 - prc: 0.7660"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7804 - tp: 2522.0000 - fp: 1185.0000 - tn: 2904.0000 - fn: 1581.0000 - accuracy: 0.6624 - precision: 0.6803 - recall: 0.6147 - auc: 0.6886 - prc: 0.7799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7692 - tp: 3871.0000 - fp: 1757.0000 - tn: 4332.0000 - fn: 2328.0000 - accuracy: 0.6676 - precision: 0.6878 - recall: 0.6245 - auc: 0.6949 - prc: 0.7874"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7349 - tp: 5981.0000 - fp: 2576.0000 - tn: 6533.0000 - fn: 3342.0000 - accuracy: 0.6789 - precision: 0.6990 - recall: 0.6415 - auc: 0.7114 - prc: 0.8008"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.7105 - tp: 8104.0000 - fp: 3475.0000 - tn: 8713.0000 - fn: 4284.0000 - accuracy: 0.6843 - precision: 0.6999 - recall: 0.6542 - auc: 0.7228 - prc: 0.8084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6922 - tp: 10276.0000 - fp: 4289.0000 - tn: 10939.0000 - fn: 5216.0000 - accuracy: 0.6906 - precision: 0.7055 - recall: 0.6633 - auc: 0.7315 - 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",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.6772 - tp: 12491.0000 - fp: 5107.0000 - tn: 13127.0000 - fn: 6139.0000 - accuracy: 0.6949 - precision: 0.7098 - recall: 0.6705 - auc: 0.7390 - prc: 0.8207"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.6680 - tp: 13969.0000 - fp: 5680.0000 - tn: 14619.0000 - fn: 6692.0000 - accuracy: 0.6979 - precision: 0.7109 - recall: 0.6761 - auc: 0.7440 - prc: 0.8238 - val_loss: 0.4738 - val_tp: 57.0000 - val_fp: 7346.0000 - val_tn: 38154.0000 - val_fn: 12.0000 - val_accuracy: 0.8385 - val_precision: 0.0077 - val_recall: 0.8261 - val_auc: 0.8709 - val_prc: 0.3997\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.5706 - tp: 732.0000 - fp: 299.0000 - tn: 747.0000 - fn: 270.0000 - accuracy: 0.7222 - precision: 0.7100 - recall: 0.7305 - auc: 0.7961 - prc: 0.8538"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5462 - tp: 3772.0000 - fp: 1337.0000 - tn: 3820.0000 - fn: 1311.0000 - accuracy: 0.7414 - precision: 0.7383 - recall: 0.7421 - auc: 0.8070 - prc: 0.8642"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5393 - tp: 6135.0000 - fp: 2175.0000 - tn: 6002.0000 - fn: 2072.0000 - accuracy: 0.7408 - precision: 0.7383 - recall: 0.7475 - auc: 0.8112 - prc: 0.8688"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5349 - tp: 8473.0000 - fp: 3016.0000 - tn: 8246.0000 - fn: 2793.0000 - accuracy: 0.7421 - precision: 0.7375 - recall: 0.7521 - auc: 0.8140 - prc: 0.8710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5287 - tp: 10821.0000 - fp: 3815.0000 - tn: 10555.0000 - fn: 3481.0000 - accuracy: 0.7455 - precision: 0.7393 - recall: 0.7566 - auc: 0.8182 - prc: 0.8735"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5246 - tp: 13260.0000 - fp: 4588.0000 - tn: 12800.0000 - fn: 4168.0000 - accuracy: 0.7485 - precision: 0.7429 - recall: 0.7608 - auc: 0.8211 - prc: 0.8761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5201 - tp: 15755.0000 - fp: 5337.0000 - tn: 15024.0000 - fn: 4844.0000 - accuracy: 0.7514 - precision: 0.7470 - recall: 0.7648 - auc: 0.8243 - prc: 0.8789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.5201 - tp: 15755.0000 - fp: 5337.0000 - tn: 15024.0000 - fn: 4844.0000 - accuracy: 0.7514 - precision: 0.7470 - recall: 0.7648 - auc: 0.8243 - prc: 0.8789 - val_loss: 0.4438 - val_tp: 56.0000 - val_fp: 5961.0000 - val_tn: 39539.0000 - val_fn: 13.0000 - val_accuracy: 0.8689 - val_precision: 0.0093 - val_recall: 0.8116 - val_auc: 0.8914 - val_prc: 0.4917\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4951 - tp: 815.0000 - fp: 285.0000 - tn: 733.0000 - fn: 215.0000 - accuracy: 0.7559 - precision: 0.7409 - recall: 0.7913 - auc: 0.8421 - prc: 0.8916"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4718 - tp: 4054.0000 - fp: 1300.0000 - tn: 3830.0000 - fn: 1056.0000 - accuracy: 0.7699 - precision: 0.7572 - recall: 0.7933 - auc: 0.8531 - prc: 0.8975"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4697 - tp: 6471.0000 - fp: 2087.0000 - tn: 6161.0000 - fn: 1665.0000 - accuracy: 0.7710 - precision: 0.7561 - recall: 0.7954 - auc: 0.8538 - prc: 0.8976"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4649 - tp: 8930.0000 - fp: 2787.0000 - tn: 8537.0000 - fn: 2274.0000 - accuracy: 0.7753 - precision: 0.7621 - recall: 0.7970 - auc: 0.8569 - prc: 0.9001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4593 - tp: 11397.0000 - fp: 3482.0000 - tn: 10943.0000 - fn: 2850.0000 - accuracy: 0.7792 - precision: 0.7660 - recall: 0.8000 - auc: 0.8602 - prc: 0.9022"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4555 - tp: 13818.0000 - fp: 4136.0000 - tn: 13403.0000 - fn: 3459.0000 - accuracy: 0.7819 - precision: 0.7696 - recall: 0.7998 - auc: 0.8623 - prc: 0.9034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4520 - tp: 16277.0000 - fp: 4793.0000 - tn: 15830.0000 - fn: 4060.0000 - accuracy: 0.7839 - precision: 0.7725 - recall: 0.8004 - auc: 0.8638 - prc: 0.9046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.4520 - tp: 16277.0000 - fp: 4793.0000 - tn: 15830.0000 - fn: 4060.0000 - accuracy: 0.7839 - precision: 0.7725 - recall: 0.8004 - auc: 0.8638 - prc: 0.9046 - val_loss: 0.4042 - val_tp: 57.0000 - val_fp: 4418.0000 - val_tn: 41082.0000 - val_fn: 12.0000 - val_accuracy: 0.9028 - val_precision: 0.0127 - val_recall: 0.8261 - val_auc: 0.9071 - val_prc: 0.5734\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4242 - tp: 853.0000 - fp: 214.0000 - tn: 775.0000 - fn: 206.0000 - accuracy: 0.7949 - precision: 0.7994 - recall: 0.8055 - auc: 0.8774 - prc: 0.9177"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4153 - tp: 4235.0000 - fp: 1015.0000 - tn: 4045.0000 - fn: 945.0000 - accuracy: 0.8086 - precision: 0.8067 - recall: 0.8176 - auc: 0.8844 - prc: 0.9204"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4122 - tp: 6824.0000 - fp: 1602.0000 - tn: 6449.0000 - fn: 1509.0000 - accuracy: 0.8101 - precision: 0.8099 - recall: 0.8189 - auc: 0.8851 - prc: 0.9219"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4073 - tp: 9402.0000 - fp: 2174.0000 - tn: 8912.0000 - fn: 2040.0000 - accuracy: 0.8129 - precision: 0.8122 - recall: 0.8217 - auc: 0.8876 - prc: 0.9236"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4072 - tp: 11087.0000 - fp: 2566.0000 - tn: 10563.0000 - fn: 2408.0000 - accuracy: 0.8132 - precision: 0.8121 - recall: 0.8216 - auc: 0.8877 - prc: 0.9235"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4050 - tp: 12792.0000 - fp: 2939.0000 - tn: 12210.0000 - fn: 2779.0000 - accuracy: 0.8139 - precision: 0.8132 - recall: 0.8215 - auc: 0.8883 - prc: 0.9239"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4040 - tp: 14505.0000 - fp: 3313.0000 - tn: 13860.0000 - fn: 3138.0000 - accuracy: 0.8147 - precision: 0.8141 - recall: 0.8221 - auc: 0.8887 - prc: 0.9243"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4020 - tp: 16227.0000 - fp: 3659.0000 - tn: 15523.0000 - fn: 3503.0000 - accuracy: 0.8159 - precision: 0.8160 - recall: 0.8225 - auc: 0.8892 - prc: 0.9248"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.4011 - tp: 17099.0000 - fp: 3860.0000 - tn: 16322.0000 - fn: 3679.0000 - accuracy: 0.8159 - precision: 0.8158 - recall: 0.8229 - auc: 0.8896 - prc: 0.9251 - val_loss: 0.3656 - val_tp: 57.0000 - val_fp: 3142.0000 - val_tn: 42358.0000 - val_fn: 12.0000 - val_accuracy: 0.9308 - val_precision: 0.0178 - val_recall: 0.8261 - val_auc: 0.9215 - val_prc: 0.5999\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.4019 - tp: 803.0000 - fp: 207.0000 - tn: 860.0000 - fn: 178.0000 - accuracy: 0.8120 - precision: 0.7950 - recall: 0.8186 - auc: 0.8877 - prc: 0.9199"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3873 - tp: 4187.0000 - fp: 992.0000 - tn: 4222.0000 - fn: 839.0000 - accuracy: 0.8212 - precision: 0.8085 - recall: 0.8331 - auc: 0.8997 - prc: 0.9284"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3840 - tp: 6748.0000 - fp: 1519.0000 - tn: 6787.0000 - fn: 1330.0000 - accuracy: 0.8261 - precision: 0.8163 - recall: 0.8354 - auc: 0.9014 - prc: 0.9299"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3768 - tp: 9339.0000 - fp: 2014.0000 - tn: 9365.0000 - fn: 1810.0000 - accuracy: 0.8303 - precision: 0.8226 - recall: 0.8377 - auc: 0.9047 - prc: 0.9327"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3749 - tp: 11854.0000 - fp: 2497.0000 - tn: 12009.0000 - fn: 2312.0000 - accuracy: 0.8323 - precision: 0.8260 - recall: 0.8368 - auc: 0.9051 - prc: 0.9328"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3720 - tp: 14427.0000 - fp: 3000.0000 - tn: 14601.0000 - fn: 2788.0000 - accuracy: 0.8338 - precision: 0.8279 - recall: 0.8380 - auc: 0.9066 - prc: 0.9337"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3698 - tp: 17030.0000 - fp: 3437.0000 - tn: 17200.0000 - fn: 3293.0000 - accuracy: 0.8357 - precision: 0.8321 - recall: 0.8380 - auc: 0.9073 - prc: 0.9346"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3698 - tp: 17030.0000 - fp: 3437.0000 - tn: 17200.0000 - fn: 3293.0000 - accuracy: 0.8357 - precision: 0.8321 - recall: 0.8380 - auc: 0.9073 - prc: 0.9346 - val_loss: 0.3284 - val_tp: 57.0000 - val_fp: 2106.0000 - val_tn: 43394.0000 - val_fn: 12.0000 - val_accuracy: 0.9535 - val_precision: 0.0264 - val_recall: 0.8261 - val_auc: 0.9342 - val_prc: 0.6209\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3501 - tp: 853.0000 - fp: 159.0000 - tn: 879.0000 - fn: 157.0000 - accuracy: 0.8457 - precision: 0.8429 - recall: 0.8446 - auc: 0.9166 - prc: 0.9393"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3551 - tp: 4376.0000 - fp: 744.0000 - tn: 4300.0000 - fn: 820.0000 - accuracy: 0.8473 - precision: 0.8547 - recall: 0.8422 - auc: 0.9141 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.3485 - tp: 7011.0000 - fp: 1143.0000 - tn: 6922.0000 - fn: 1308.0000 - accuracy: 0.8504 - precision: 0.8598 - recall: 0.8428 - auc: 0.9160 - prc: 0.9423"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3491 - tp: 9648.0000 - fp: 1587.0000 - tn: 9496.0000 - fn: 1797.0000 - accuracy: 0.8498 - precision: 0.8587 - recall: 0.8430 - auc: 0.9156 - prc: 0.9420"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3501 - tp: 12259.0000 - fp: 2027.0000 - tn: 12116.0000 - fn: 2270.0000 - accuracy: 0.8501 - precision: 0.8581 - recall: 0.8438 - auc: 0.9154 - 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",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3475 - tp: 14819.0000 - fp: 2416.0000 - tn: 14828.0000 - fn: 2753.0000 - accuracy: 0.8515 - precision: 0.8598 - recall: 0.8433 - auc: 0.9163 - prc: 0.9420"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3450 - tp: 17393.0000 - fp: 2816.0000 - tn: 17557.0000 - fn: 3194.0000 - accuracy: 0.8533 - precision: 0.8607 - recall: 0.8449 - auc: 0.9176 - prc: 0.9426"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.3450 - tp: 17393.0000 - fp: 2816.0000 - tn: 17557.0000 - fn: 3194.0000 - accuracy: 0.8533 - precision: 0.8607 - recall: 0.8449 - auc: 0.9176 - prc: 0.9426 - val_loss: 0.2964 - val_tp: 56.0000 - val_fp: 1409.0000 - val_tn: 44091.0000 - val_fn: 13.0000 - val_accuracy: 0.9688 - val_precision: 0.0382 - val_recall: 0.8116 - val_auc: 0.9453 - val_prc: 0.6271\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3289 - tp: 885.0000 - fp: 125.0000 - tn: 879.0000 - fn: 159.0000 - accuracy: 0.8613 - precision: 0.8762 - recall: 0.8477 - auc: 0.9222 - prc: 0.9476"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3307 - tp: 4360.0000 - fp: 683.0000 - tn: 4437.0000 - fn: 760.0000 - accuracy: 0.8591 - precision: 0.8646 - recall: 0.8516 - auc: 0.9228 - prc: 0.9466"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3309 - tp: 6973.0000 - fp: 1072.0000 - tn: 7106.0000 - fn: 1233.0000 - accuracy: 0.8593 - precision: 0.8667 - recall: 0.8497 - auc: 0.9229 - prc: 0.9465"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3279 - tp: 9565.0000 - fp: 1451.0000 - tn: 9837.0000 - fn: 1675.0000 - accuracy: 0.8612 - precision: 0.8683 - recall: 0.8510 - auc: 0.9242 - prc: 0.9472"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3262 - tp: 12241.0000 - fp: 1801.0000 - tn: 12491.0000 - fn: 2139.0000 - accuracy: 0.8626 - precision: 0.8717 - recall: 0.8513 - auc: 0.9248 - 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\b\b\b\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3243 - tp: 14815.0000 - fp: 2183.0000 - tn: 15259.0000 - fn: 2559.0000 - accuracy: 0.8638 - precision: 0.8716 - recall: 0.8527 - auc: 0.9261 - 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",
      "20/20 [==============================] - ETA: 0s - loss: 0.3227 - tp: 17476.0000 - fp: 2488.0000 - tn: 17993.0000 - fn: 3003.0000 - accuracy: 0.8659 - precision: 0.8754 - recall: 0.8534 - auc: 0.9266 - 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 29ms/step - loss: 0.3227 - tp: 17476.0000 - fp: 2488.0000 - tn: 17993.0000 - fn: 3003.0000 - accuracy: 0.8659 - precision: 0.8754 - recall: 0.8534 - auc: 0.9266 - prc: 0.9487 - val_loss: 0.2685 - val_tp: 57.0000 - val_fp: 1014.0000 - val_tn: 44486.0000 - val_fn: 12.0000 - val_accuracy: 0.9775 - val_precision: 0.0532 - val_recall: 0.8261 - val_auc: 0.9538 - val_prc: 0.6388\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.3184 - tp: 859.0000 - fp: 114.0000 - tn: 921.0000 - fn: 154.0000 - accuracy: 0.8691 - precision: 0.8828 - recall: 0.8480 - auc: 0.9273 - prc: 0.9481"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3051 - tp: 4339.0000 - fp: 577.0000 - tn: 4583.0000 - fn: 741.0000 - accuracy: 0.8713 - precision: 0.8826 - recall: 0.8541 - auc: 0.9335 - prc: 0.9523"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.3023 - tp: 7023.0000 - fp: 889.0000 - tn: 7317.0000 - fn: 1155.0000 - accuracy: 0.8752 - precision: 0.8876 - recall: 0.8588 - auc: 0.9350 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.3020 - tp: 9698.0000 - fp: 1221.0000 - tn: 10044.0000 - fn: 1565.0000 - accuracy: 0.8763 - precision: 0.8882 - recall: 0.8610 - auc: 0.9354 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.3013 - tp: 12344.0000 - fp: 1528.0000 - tn: 12789.0000 - fn: 2011.0000 - accuracy: 0.8766 - precision: 0.8899 - recall: 0.8599 - auc: 0.9356 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.3013 - tp: 14971.0000 - fp: 1842.0000 - tn: 15566.0000 - fn: 2437.0000 - accuracy: 0.8771 - precision: 0.8904 - recall: 0.8600 - auc: 0.9355 - 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 [==============================] - ETA: 0s - loss: 0.3001 - tp: 17545.0000 - fp: 2111.0000 - tn: 18430.0000 - fn: 2874.0000 - accuracy: 0.8783 - precision: 0.8926 - recall: 0.8592 - auc: 0.9358 - 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: 0.3001 - tp: 17545.0000 - fp: 2111.0000 - tn: 18430.0000 - fn: 2874.0000 - accuracy: 0.8783 - precision: 0.8926 - recall: 0.8592 - auc: 0.9358 - prc: 0.9542 - val_loss: 0.2439 - val_tp: 57.0000 - val_fp: 766.0000 - val_tn: 44734.0000 - val_fn: 12.0000 - val_accuracy: 0.9829 - val_precision: 0.0693 - val_recall: 0.8261 - val_auc: 0.9601 - val_prc: 0.6474\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2966 - tp: 889.0000 - fp: 101.0000 - tn: 918.0000 - fn: 140.0000 - accuracy: 0.8823 - precision: 0.8980 - recall: 0.8639 - auc: 0.9381 - prc: 0.9560"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2938 - tp: 4449.0000 - fp: 511.0000 - tn: 4573.0000 - fn: 707.0000 - accuracy: 0.8811 - precision: 0.8970 - recall: 0.8629 - auc: 0.9389 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2938 - tp: 7092.0000 - fp: 796.0000 - tn: 7354.0000 - fn: 1142.0000 - accuracy: 0.8817 - precision: 0.8991 - recall: 0.8613 - auc: 0.9386 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2904 - tp: 9697.0000 - fp: 1060.0000 - tn: 10207.0000 - fn: 1564.0000 - accuracy: 0.8835 - precision: 0.9015 - recall: 0.8611 - auc: 0.9393 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2877 - tp: 12288.0000 - fp: 1327.0000 - tn: 13072.0000 - fn: 1985.0000 - accuracy: 0.8845 - precision: 0.9025 - recall: 0.8609 - auc: 0.9402 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2857 - tp: 14942.0000 - fp: 1599.0000 - tn: 15859.0000 - fn: 2416.0000 - accuracy: 0.8847 - precision: 0.9033 - recall: 0.8608 - auc: 0.9410 - 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\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2841 - tp: 17588.0000 - fp: 1838.0000 - tn: 18720.0000 - fn: 2814.0000 - accuracy: 0.8864 - precision: 0.9054 - recall: 0.8621 - auc: 0.9417 - 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\r",
      "20/20 [==============================] - 1s 29ms/step - loss: 0.2841 - tp: 17588.0000 - fp: 1838.0000 - tn: 18720.0000 - fn: 2814.0000 - accuracy: 0.8864 - precision: 0.9054 - recall: 0.8621 - auc: 0.9417 - prc: 0.9580 - val_loss: 0.2229 - val_tp: 57.0000 - val_fp: 672.0000 - val_tn: 44828.0000 - val_fn: 12.0000 - val_accuracy: 0.9850 - val_precision: 0.0782 - val_recall: 0.8261 - val_auc: 0.9649 - val_prc: 0.6646\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2776 - tp: 823.0000 - fp: 94.0000 - tn: 998.0000 - fn: 133.0000 - accuracy: 0.8892 - precision: 0.8975 - recall: 0.8609 - auc: 0.9444 - prc: 0.9558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 4441.0000 - fp: 413.0000 - tn: 4697.0000 - fn: 689.0000 - accuracy: 0.8924 - precision: 0.9149 - recall: 0.8657 - auc: 0.9450 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2735 - tp: 7176.0000 - fp: 665.0000 - tn: 7442.0000 - fn: 1101.0000 - accuracy: 0.8922 - precision: 0.9152 - recall: 0.8670 - auc: 0.9458 - prc: 0.9613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2729 - tp: 9813.0000 - fp: 916.0000 - tn: 10300.0000 - fn: 1499.0000 - accuracy: 0.8928 - precision: 0.9146 - recall: 0.8675 - auc: 0.9458 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2722 - tp: 12427.0000 - fp: 1159.0000 - tn: 13188.0000 - fn: 1898.0000 - accuracy: 0.8934 - precision: 0.9147 - recall: 0.8675 - auc: 0.9463 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2706 - tp: 15099.0000 - fp: 1390.0000 - tn: 16043.0000 - fn: 2284.0000 - accuracy: 0.8945 - precision: 0.9157 - recall: 0.8686 - auc: 0.9469 - 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\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2695 - tp: 17684.0000 - fp: 1626.0000 - tn: 18962.0000 - fn: 2688.0000 - accuracy: 0.8947 - precision: 0.9158 - recall: 0.8681 - auc: 0.9472 - 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\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.2695 - tp: 17684.0000 - fp: 1626.0000 - tn: 18962.0000 - fn: 2688.0000 - accuracy: 0.8947 - precision: 0.9158 - recall: 0.8681 - auc: 0.9472 - prc: 0.9616 - val_loss: 0.2051 - val_tp: 57.0000 - val_fp: 631.0000 - val_tn: 44869.0000 - val_fn: 12.0000 - val_accuracy: 0.9859 - val_precision: 0.0828 - val_recall: 0.8261 - val_auc: 0.9677 - val_prc: 0.6582\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2680 - tp: 911.0000 - fp: 87.0000 - tn: 915.0000 - fn: 135.0000 - accuracy: 0.8916 - precision: 0.9128 - recall: 0.8709 - auc: 0.9473 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2651 - tp: 4430.0000 - fp: 397.0000 - tn: 4750.0000 - fn: 663.0000 - accuracy: 0.8965 - precision: 0.9178 - recall: 0.8698 - auc: 0.9489 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2634 - tp: 7118.0000 - fp: 609.0000 - tn: 7592.0000 - fn: 1065.0000 - accuracy: 0.8978 - precision: 0.9212 - recall: 0.8699 - auc: 0.9491 - 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\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2628 - tp: 8929.0000 - fp: 774.0000 - tn: 9441.0000 - fn: 1336.0000 - accuracy: 0.8970 - precision: 0.9202 - recall: 0.8698 - auc: 0.9492 - 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",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2627 - tp: 11602.0000 - fp: 991.0000 - tn: 12299.0000 - fn: 1732.0000 - accuracy: 0.8977 - precision: 0.9213 - recall: 0.8701 - auc: 0.9493 - 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",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2618 - tp: 14249.0000 - fp: 1199.0000 - tn: 15209.0000 - fn: 2111.0000 - accuracy: 0.8990 - precision: 0.9224 - recall: 0.8710 - auc: 0.9498 - 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\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2611 - tp: 16929.0000 - fp: 1418.0000 - tn: 18059.0000 - fn: 2506.0000 - accuracy: 0.8992 - precision: 0.9227 - recall: 0.8711 - auc: 0.9499 - 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\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.2608 - tp: 17838.0000 - fp: 1483.0000 - tn: 19004.0000 - fn: 2635.0000 - accuracy: 0.8995 - precision: 0.9232 - recall: 0.8713 - auc: 0.9500 - prc: 0.9639 - val_loss: 0.1904 - val_tp: 57.0000 - val_fp: 619.0000 - val_tn: 44881.0000 - val_fn: 12.0000 - val_accuracy: 0.9862 - val_precision: 0.0843 - val_recall: 0.8261 - val_auc: 0.9692 - val_prc: 0.6674\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2568 - tp: 872.0000 - fp: 74.0000 - tn: 980.0000 - fn: 122.0000 - accuracy: 0.9043 - precision: 0.9218 - recall: 0.8773 - auc: 0.9544 - 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\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2546 - tp: 3553.0000 - fp: 290.0000 - tn: 3847.0000 - fn: 502.0000 - accuracy: 0.9033 - precision: 0.9245 - recall: 0.8762 - auc: 0.9535 - 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\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.2535 - tp: 6214.0000 - fp: 494.0000 - tn: 6723.0000 - fn: 905.0000 - accuracy: 0.9024 - precision: 0.9264 - recall: 0.8729 - auc: 0.9536 - 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\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2517 - tp: 8912.0000 - fp: 709.0000 - tn: 9560.0000 - fn: 1299.0000 - accuracy: 0.9020 - precision: 0.9263 - recall: 0.8728 - auc: 0.9536 - prc: 0.9661"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2499 - tp: 10735.0000 - fp: 838.0000 - tn: 11454.0000 - fn: 1549.0000 - accuracy: 0.9029 - precision: 0.9276 - recall: 0.8739 - auc: 0.9543 - 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",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.2498 - tp: 13484.0000 - fp: 1038.0000 - tn: 14253.0000 - fn: 1945.0000 - accuracy: 0.9029 - precision: 0.9285 - recall: 0.8739 - auc: 0.9542 - prc: 0.9668"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2480 - tp: 16157.0000 - fp: 1233.0000 - tn: 17160.0000 - fn: 2314.0000 - accuracy: 0.9038 - precision: 0.9291 - recall: 0.8747 - auc: 0.9548 - prc: 0.9672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2480 - tp: 17914.0000 - fp: 1354.0000 - tn: 19123.0000 - fn: 2569.0000 - accuracy: 0.9042 - precision: 0.9297 - recall: 0.8746 - auc: 0.9548 - prc: 0.9670 - val_loss: 0.1775 - val_tp: 58.0000 - val_fp: 600.0000 - val_tn: 44900.0000 - val_fn: 11.0000 - val_accuracy: 0.9866 - val_precision: 0.0881 - val_recall: 0.8406 - val_auc: 0.9696 - val_prc: 0.6689\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2357 - tp: 919.0000 - fp: 67.0000 - tn: 940.0000 - fn: 122.0000 - accuracy: 0.9077 - precision: 0.9320 - recall: 0.8828 - auc: 0.9587 - prc: 0.9702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2433 - tp: 4421.0000 - fp: 324.0000 - tn: 4872.0000 - fn: 623.0000 - accuracy: 0.9075 - precision: 0.9317 - recall: 0.8765 - auc: 0.9561 - prc: 0.9674"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2427 - tp: 7179.0000 - fp: 484.0000 - tn: 7719.0000 - fn: 1002.0000 - accuracy: 0.9093 - precision: 0.9368 - recall: 0.8775 - auc: 0.9562 - 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: 0.2424 - tp: 9848.0000 - fp: 674.0000 - tn: 10635.0000 - fn: 1371.0000 - accuracy: 0.9092 - precision: 0.9359 - recall: 0.8778 - auc: 0.9563 - 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\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2403 - tp: 12527.0000 - fp: 847.0000 - tn: 13577.0000 - fn: 1721.0000 - accuracy: 0.9104 - precision: 0.9367 - recall: 0.8792 - auc: 0.9575 - prc: 0.9686"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2382 - tp: 15168.0000 - fp: 1025.0000 - tn: 16545.0000 - fn: 2078.0000 - accuracy: 0.9109 - precision: 0.9367 - recall: 0.8795 - auc: 0.9584 - 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\b\b\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2393 - tp: 17851.0000 - fp: 1228.0000 - tn: 19433.0000 - fn: 2448.0000 - accuracy: 0.9103 - precision: 0.9356 - recall: 0.8794 - auc: 0.9580 - prc: 0.9687"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.2393 - tp: 17851.0000 - fp: 1228.0000 - tn: 19433.0000 - fn: 2448.0000 - accuracy: 0.9103 - precision: 0.9356 - recall: 0.8794 - auc: 0.9580 - prc: 0.9687 - val_loss: 0.1656 - val_tp: 59.0000 - val_fp: 579.0000 - val_tn: 44921.0000 - val_fn: 10.0000 - val_accuracy: 0.9871 - val_precision: 0.0925 - val_recall: 0.8551 - val_auc: 0.9706 - val_prc: 0.6725\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2224 - tp: 880.0000 - fp: 56.0000 - tn: 1007.0000 - fn: 105.0000 - accuracy: 0.9214 - precision: 0.9402 - recall: 0.8934 - auc: 0.9620 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2307 - tp: 4513.0000 - fp: 304.0000 - tn: 4817.0000 - fn: 606.0000 - accuracy: 0.9111 - precision: 0.9369 - recall: 0.8816 - auc: 0.9613 - prc: 0.9713"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2325 - tp: 7229.0000 - fp: 479.0000 - tn: 7704.0000 - fn: 972.0000 - accuracy: 0.9114 - precision: 0.9379 - recall: 0.8815 - auc: 0.9602 - prc: 0.9706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2328 - tp: 9951.0000 - fp: 647.0000 - tn: 10600.0000 - fn: 1330.0000 - accuracy: 0.9122 - precision: 0.9390 - recall: 0.8821 - auc: 0.9602 - prc: 0.9703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2314 - tp: 12594.0000 - fp: 805.0000 - tn: 13574.0000 - fn: 1699.0000 - accuracy: 0.9127 - precision: 0.9399 - recall: 0.8811 - auc: 0.9605 - prc: 0.9704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2306 - tp: 15273.0000 - fp: 961.0000 - tn: 16505.0000 - fn: 2077.0000 - accuracy: 0.9127 - precision: 0.9408 - recall: 0.8803 - auc: 0.9607 - prc: 0.9706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2296 - tp: 17997.0000 - fp: 1116.0000 - tn: 19406.0000 - fn: 2441.0000 - accuracy: 0.9132 - precision: 0.9416 - recall: 0.8806 - auc: 0.9613 - prc: 0.9710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2296 - tp: 17997.0000 - fp: 1116.0000 - tn: 19406.0000 - fn: 2441.0000 - accuracy: 0.9132 - precision: 0.9416 - recall: 0.8806 - auc: 0.9613 - prc: 0.9710 - val_loss: 0.1556 - val_tp: 58.0000 - val_fp: 587.0000 - val_tn: 44913.0000 - val_fn: 11.0000 - val_accuracy: 0.9869 - val_precision: 0.0899 - val_recall: 0.8406 - val_auc: 0.9713 - val_prc: 0.6760\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2328 - tp: 900.0000 - fp: 59.0000 - tn: 966.0000 - fn: 123.0000 - accuracy: 0.9111 - precision: 0.9385 - recall: 0.8798 - auc: 0.9596 - prc: 0.9704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2270 - tp: 4465.0000 - fp: 265.0000 - tn: 4891.0000 - fn: 619.0000 - accuracy: 0.9137 - precision: 0.9440 - recall: 0.8782 - auc: 0.9615 - prc: 0.9710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2261 - tp: 7196.0000 - fp: 433.0000 - tn: 7787.0000 - fn: 968.0000 - accuracy: 0.9145 - precision: 0.9432 - recall: 0.8814 - auc: 0.9623 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2256 - tp: 9886.0000 - fp: 610.0000 - tn: 10713.0000 - fn: 1319.0000 - accuracy: 0.9144 - precision: 0.9419 - recall: 0.8823 - auc: 0.9624 - 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\b\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2232 - tp: 12656.0000 - fp: 760.0000 - tn: 13576.0000 - fn: 1680.0000 - accuracy: 0.9149 - precision: 0.9434 - recall: 0.8828 - auc: 0.9633 - prc: 0.9725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2237 - tp: 15377.0000 - fp: 912.0000 - tn: 16470.0000 - fn: 2057.0000 - accuracy: 0.9147 - precision: 0.9440 - recall: 0.8820 - auc: 0.9632 - prc: 0.9724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2228 - tp: 18079.0000 - fp: 1057.0000 - tn: 19426.0000 - fn: 2398.0000 - accuracy: 0.9156 - precision: 0.9448 - recall: 0.8829 - auc: 0.9634 - 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\b\b\b\b\b\b\r",
      "20/20 [==============================] - 1s 27ms/step - loss: 0.2228 - tp: 18079.0000 - fp: 1057.0000 - tn: 19426.0000 - fn: 2398.0000 - accuracy: 0.9156 - precision: 0.9448 - recall: 0.8829 - auc: 0.9634 - prc: 0.9726 - val_loss: 0.1474 - val_tp: 58.0000 - val_fp: 592.0000 - val_tn: 44908.0000 - val_fn: 11.0000 - val_accuracy: 0.9868 - val_precision: 0.0892 - val_recall: 0.8406 - val_auc: 0.9711 - val_prc: 0.6768\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2184 - tp: 895.0000 - fp: 53.0000 - tn: 981.0000 - fn: 119.0000 - accuracy: 0.9160 - precision: 0.9441 - recall: 0.8826 - auc: 0.9645 - prc: 0.9722"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2188 - tp: 3532.0000 - fp: 211.0000 - tn: 3964.0000 - fn: 485.0000 - accuracy: 0.9150 - precision: 0.9436 - recall: 0.8793 - auc: 0.9649 - prc: 0.9725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2168 - tp: 5380.0000 - fp: 309.0000 - tn: 5874.0000 - fn: 725.0000 - accuracy: 0.9159 - precision: 0.9457 - recall: 0.8812 - auc: 0.9659 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2188 - tp: 7188.0000 - fp: 422.0000 - tn: 7804.0000 - fn: 970.0000 - accuracy: 0.9150 - precision: 0.9445 - recall: 0.8811 - auc: 0.9652 - 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",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2183 - tp: 8963.0000 - fp: 517.0000 - tn: 9775.0000 - fn: 1225.0000 - accuracy: 0.9149 - precision: 0.9455 - recall: 0.8798 - auc: 0.9653 - 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",
      "12/20 [=================>............] - ETA: 0s - loss: 0.2184 - tp: 10842.0000 - fp: 615.0000 - tn: 11654.0000 - fn: 1465.0000 - accuracy: 0.9154 - precision: 0.9463 - recall: 0.8810 - auc: 0.9652 - 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",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2180 - tp: 12628.0000 - fp: 716.0000 - tn: 13627.0000 - fn: 1701.0000 - accuracy: 0.9157 - precision: 0.9463 - recall: 0.8813 - auc: 0.9652 - 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",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2175 - tp: 14431.0000 - fp: 832.0000 - tn: 15566.0000 - fn: 1939.0000 - accuracy: 0.9154 - precision: 0.9455 - recall: 0.8816 - auc: 0.9654 - 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",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.2162 - tp: 16234.0000 - fp: 926.0000 - tn: 17552.0000 - fn: 2152.0000 - accuracy: 0.9165 - precision: 0.9460 - recall: 0.8830 - auc: 0.9658 - prc: 0.9741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2160 - tp: 18053.0000 - fp: 1023.0000 - tn: 19497.0000 - fn: 2387.0000 - accuracy: 0.9167 - precision: 0.9464 - recall: 0.8832 - auc: 0.9657 - prc: 0.9740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2160 - tp: 18053.0000 - fp: 1023.0000 - tn: 19497.0000 - fn: 2387.0000 - accuracy: 0.9167 - precision: 0.9464 - recall: 0.8832 - auc: 0.9657 - prc: 0.9740 - val_loss: 0.1401 - val_tp: 59.0000 - val_fp: 591.0000 - val_tn: 44909.0000 - val_fn: 10.0000 - val_accuracy: 0.9868 - val_precision: 0.0908 - val_recall: 0.8551 - val_auc: 0.9711 - val_prc: 0.6801\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2190 - tp: 916.0000 - fp: 44.0000 - tn: 970.0000 - fn: 118.0000 - accuracy: 0.9209 - precision: 0.9542 - recall: 0.8859 - auc: 0.9659 - prc: 0.9744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2126 - tp: 3608.0000 - fp: 190.0000 - tn: 3934.0000 - fn: 460.0000 - accuracy: 0.9207 - precision: 0.9500 - recall: 0.8869 - auc: 0.9664 - prc: 0.9747"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.2160 - tp: 5418.0000 - fp: 286.0000 - tn: 5891.0000 - fn: 693.0000 - accuracy: 0.9203 - precision: 0.9499 - recall: 0.8866 - auc: 0.9655 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2127 - tp: 7228.0000 - fp: 378.0000 - tn: 7872.0000 - fn: 906.0000 - accuracy: 0.9216 - precision: 0.9503 - recall: 0.8886 - auc: 0.9666 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2108 - tp: 9955.0000 - fp: 520.0000 - tn: 10796.0000 - fn: 1257.0000 - accuracy: 0.9211 - precision: 0.9504 - recall: 0.8879 - auc: 0.9673 - 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: 0.2116 - tp: 12679.0000 - fp: 662.0000 - tn: 13723.0000 - fn: 1608.0000 - accuracy: 0.9208 - precision: 0.9504 - recall: 0.8875 - auc: 0.9673 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2112 - tp: 15398.0000 - fp: 833.0000 - tn: 16660.0000 - fn: 1925.0000 - accuracy: 0.9208 - precision: 0.9487 - recall: 0.8889 - auc: 0.9675 - 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\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2111 - tp: 17197.0000 - fp: 933.0000 - tn: 18637.0000 - fn: 2145.0000 - accuracy: 0.9209 - precision: 0.9485 - recall: 0.8891 - auc: 0.9676 - 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\r",
      "20/20 [==============================] - 1s 30ms/step - loss: 0.2113 - tp: 18152.0000 - fp: 986.0000 - tn: 19555.0000 - fn: 2267.0000 - accuracy: 0.9206 - precision: 0.9485 - recall: 0.8890 - auc: 0.9676 - prc: 0.9752 - val_loss: 0.1336 - val_tp: 59.0000 - val_fp: 595.0000 - val_tn: 44905.0000 - val_fn: 10.0000 - val_accuracy: 0.9867 - val_precision: 0.0902 - val_recall: 0.8551 - val_auc: 0.9709 - val_prc: 0.6806\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1985 - tp: 925.0000 - fp: 39.0000 - tn: 981.0000 - fn: 103.0000 - accuracy: 0.9307 - precision: 0.9595 - recall: 0.8998 - auc: 0.9713 - 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\r",
      " 4/20 [=====>........................] - ETA: 0s - loss: 0.2046 - tp: 3654.0000 - fp: 178.0000 - tn: 3914.0000 - fn: 446.0000 - accuracy: 0.9238 - precision: 0.9535 - recall: 0.8912 - auc: 0.9695 - 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\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.2052 - tp: 6440.0000 - fp: 314.0000 - tn: 6770.0000 - fn: 812.0000 - accuracy: 0.9215 - precision: 0.9535 - recall: 0.8880 - auc: 0.9694 - 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\r",
      "10/20 [==============>...............] - ETA: 0s - loss: 0.2066 - tp: 9180.0000 - fp: 478.0000 - tn: 9678.0000 - fn: 1144.0000 - accuracy: 0.9208 - precision: 0.9505 - recall: 0.8892 - auc: 0.9692 - 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\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.2077 - tp: 11916.0000 - fp: 638.0000 - tn: 12578.0000 - fn: 1492.0000 - accuracy: 0.9200 - precision: 0.9492 - recall: 0.8887 - auc: 0.9689 - 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\r",
      "16/20 [=======================>......] - ETA: 0s - loss: 0.2078 - tp: 14656.0000 - fp: 797.0000 - tn: 15484.0000 - fn: 1831.0000 - accuracy: 0.9198 - precision: 0.9484 - recall: 0.8889 - auc: 0.9688 - 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\r",
      "19/20 [===========================>..] - ETA: 0s - loss: 0.2068 - tp: 17354.0000 - fp: 918.0000 - tn: 18479.0000 - fn: 2161.0000 - accuracy: 0.9209 - precision: 0.9498 - recall: 0.8893 - auc: 0.9690 - 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",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.2065 - tp: 18259.0000 - fp: 955.0000 - tn: 19468.0000 - fn: 2278.0000 - accuracy: 0.9211 - precision: 0.9503 - recall: 0.8891 - auc: 0.9690 - prc: 0.9763 - val_loss: 0.1281 - val_tp: 59.0000 - val_fp: 600.0000 - val_tn: 44900.0000 - val_fn: 10.0000 - val_accuracy: 0.9866 - val_precision: 0.0895 - val_recall: 0.8551 - val_auc: 0.9701 - val_prc: 0.6708\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2065 - tp: 932.0000 - fp: 36.0000 - tn: 973.0000 - fn: 107.0000 - accuracy: 0.9302 - precision: 0.9628 - recall: 0.8970 - auc: 0.9685 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.2065 - tp: 4598.0000 - fp: 222.0000 - tn: 4863.0000 - fn: 557.0000 - accuracy: 0.9239 - precision: 0.9539 - recall: 0.8919 - auc: 0.9689 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.2051 - tp: 7374.0000 - fp: 358.0000 - tn: 7761.0000 - fn: 891.0000 - accuracy: 0.9238 - precision: 0.9537 - recall: 0.8922 - auc: 0.9694 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.2040 - tp: 10133.0000 - fp: 477.0000 - tn: 10677.0000 - fn: 1241.0000 - accuracy: 0.9237 - precision: 0.9550 - recall: 0.8909 - auc: 0.9698 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.2023 - tp: 12817.0000 - fp: 620.0000 - tn: 13678.0000 - fn: 1557.0000 - accuracy: 0.9241 - precision: 0.9539 - recall: 0.8917 - auc: 0.9703 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.2019 - tp: 15505.0000 - fp: 755.0000 - tn: 16663.0000 - fn: 1893.0000 - accuracy: 0.9239 - precision: 0.9536 - recall: 0.8912 - auc: 0.9705 - 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\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.2017 - tp: 18234.0000 - fp: 884.0000 - tn: 19611.0000 - fn: 2231.0000 - accuracy: 0.9240 - precision: 0.9538 - recall: 0.8910 - auc: 0.9705 - 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\r",
      "20/20 [==============================] - 1s 26ms/step - loss: 0.2017 - tp: 18234.0000 - fp: 884.0000 - tn: 19611.0000 - fn: 2231.0000 - accuracy: 0.9240 - precision: 0.9538 - recall: 0.8910 - auc: 0.9705 - prc: 0.9770 - val_loss: 0.1235 - val_tp: 59.0000 - val_fp: 610.0000 - val_tn: 44890.0000 - val_fn: 10.0000 - val_accuracy: 0.9864 - val_precision: 0.0882 - val_recall: 0.8551 - val_auc: 0.9696 - val_prc: 0.6711\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1951 - tp: 923.0000 - fp: 38.0000 - tn: 982.0000 - fn: 105.0000 - accuracy: 0.9302 - precision: 0.9605 - recall: 0.8979 - auc: 0.9726 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.1970 - tp: 4564.0000 - fp: 202.0000 - tn: 4906.0000 - fn: 568.0000 - accuracy: 0.9248 - precision: 0.9576 - recall: 0.8893 - auc: 0.9718 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.1961 - tp: 7282.0000 - fp: 312.0000 - tn: 7883.0000 - fn: 907.0000 - accuracy: 0.9256 - precision: 0.9589 - recall: 0.8892 - auc: 0.9720 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.1949 - tp: 9989.0000 - fp: 441.0000 - tn: 10874.0000 - fn: 1224.0000 - accuracy: 0.9261 - precision: 0.9577 - recall: 0.8908 - auc: 0.9725 - 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\r",
      "13/20 [==================>...........] - ETA: 0s - loss: 0.1958 - tp: 11772.0000 - fp: 522.0000 - tn: 12876.0000 - fn: 1454.0000 - accuracy: 0.9258 - precision: 0.9575 - recall: 0.8901 - auc: 0.9722 - 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\r",
      "15/20 [=====================>........] - ETA: 0s - loss: 0.1954 - tp: 13592.0000 - fp: 613.0000 - tn: 14852.0000 - fn: 1663.0000 - accuracy: 0.9259 - precision: 0.9568 - recall: 0.8910 - auc: 0.9724 - 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\r",
      "18/20 [==========================>...] - ETA: 0s - loss: 0.1958 - tp: 16312.0000 - fp: 757.0000 - tn: 17811.0000 - fn: 1984.0000 - accuracy: 0.9256 - precision: 0.9557 - recall: 0.8916 - auc: 0.9723 - 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\r",
      "20/20 [==============================] - 1s 28ms/step - loss: 0.1950 - tp: 18137.0000 - fp: 831.0000 - tn: 19777.0000 - fn: 2215.0000 - accuracy: 0.9256 - precision: 0.9562 - recall: 0.8912 - auc: 0.9726 - prc: 0.9783 - val_loss: 0.1188 - val_tp: 59.0000 - val_fp: 614.0000 - val_tn: 44886.0000 - val_fn: 10.0000 - val_accuracy: 0.9863 - val_precision: 0.0877 - val_recall: 0.8551 - val_auc: 0.9693 - val_prc: 0.6716\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.2021 - tp: 933.0000 - fp: 57.0000 - tn: 959.0000 - fn: 99.0000 - accuracy: 0.9238 - precision: 0.9424 - recall: 0.9041 - auc: 0.9703 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.1959 - tp: 4547.0000 - fp: 219.0000 - tn: 4921.0000 - fn: 553.0000 - accuracy: 0.9246 - precision: 0.9540 - recall: 0.8916 - auc: 0.9724 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.1936 - tp: 7335.0000 - fp: 343.0000 - tn: 7819.0000 - fn: 887.0000 - accuracy: 0.9249 - precision: 0.9553 - recall: 0.8921 - auc: 0.9730 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.1921 - tp: 10125.0000 - fp: 446.0000 - tn: 10741.0000 - fn: 1216.0000 - accuracy: 0.9262 - precision: 0.9578 - recall: 0.8928 - auc: 0.9733 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.1918 - tp: 12890.0000 - fp: 569.0000 - tn: 13666.0000 - fn: 1547.0000 - accuracy: 0.9262 - precision: 0.9577 - recall: 0.8928 - auc: 0.9736 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.1915 - tp: 15669.0000 - fp: 707.0000 - tn: 16572.0000 - fn: 1868.0000 - accuracy: 0.9260 - precision: 0.9568 - recall: 0.8935 - auc: 0.9737 - 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\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.1923 - tp: 18425.0000 - fp: 830.0000 - tn: 19529.0000 - fn: 2176.0000 - accuracy: 0.9266 - precision: 0.9569 - recall: 0.8944 - auc: 0.9733 - 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\r",
      "20/20 [==============================] - 1s 27ms/step - loss: 0.1923 - tp: 18425.0000 - fp: 830.0000 - tn: 19529.0000 - fn: 2176.0000 - accuracy: 0.9266 - precision: 0.9569 - recall: 0.8944 - auc: 0.9733 - prc: 0.9794 - val_loss: 0.1152 - val_tp: 59.0000 - val_fp: 622.0000 - val_tn: 44878.0000 - val_fn: 10.0000 - val_accuracy: 0.9861 - val_precision: 0.0866 - val_recall: 0.8551 - val_auc: 0.9692 - val_prc: 0.6720\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 23/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1872 - tp: 916.0000 - fp: 40.0000 - tn: 980.0000 - fn: 112.0000 - accuracy: 0.9258 - precision: 0.9582 - recall: 0.8911 - auc: 0.9736 - 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: 0.1869 - tp: 4586.0000 - fp: 209.0000 - tn: 4921.0000 - fn: 524.0000 - accuracy: 0.9284 - precision: 0.9564 - recall: 0.8975 - auc: 0.9746 - prc: 0.9802"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1899 - tp: 7278.0000 - fp: 328.0000 - tn: 7928.0000 - fn: 850.0000 - accuracy: 0.9281 - precision: 0.9569 - recall: 0.8954 - auc: 0.9738 - 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\r",
      "11/20 [===============>..............] - ETA: 0s - loss: 0.1905 - tp: 10026.0000 - fp: 457.0000 - tn: 10861.0000 - fn: 1184.0000 - accuracy: 0.9272 - precision: 0.9564 - recall: 0.8944 - auc: 0.9737 - 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\r",
      "14/20 [====================>.........] - ETA: 0s - loss: 0.1895 - tp: 12758.0000 - fp: 574.0000 - tn: 13854.0000 - fn: 1486.0000 - accuracy: 0.9282 - precision: 0.9569 - recall: 0.8957 - auc: 0.9742 - 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\r",
      "17/20 [========================>.....] - ETA: 0s - loss: 0.1896 - tp: 15585.0000 - fp: 688.0000 - tn: 16727.0000 - fn: 1816.0000 - accuracy: 0.9281 - precision: 0.9577 - recall: 0.8956 - auc: 0.9741 - 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\r",
      "20/20 [==============================] - ETA: 0s - loss: 0.1886 - tp: 18374.0000 - fp: 806.0000 - tn: 19662.0000 - fn: 2118.0000 - accuracy: 0.9286 - precision: 0.9580 - recall: 0.8966 - auc: 0.9745 - prc: 0.9799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.1886 - tp: 18374.0000 - fp: 806.0000 - tn: 19662.0000 - fn: 2118.0000 - accuracy: 0.9286 - precision: 0.9580 - recall: 0.8966 - auc: 0.9745 - prc: 0.9799 - val_loss: 0.1117 - val_tp: 59.0000 - val_fp: 609.0000 - val_tn: 44891.0000 - val_fn: 10.0000 - val_accuracy: 0.9864 - val_precision: 0.0883 - val_recall: 0.8551 - val_auc: 0.9687 - val_prc: 0.6724\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1941 - tp: 894.0000 - fp: 40.0000 - tn: 1010.0000 - fn: 104.0000 - accuracy: 0.9297 - precision: 0.9572 - recall: 0.8958 - auc: 0.9743 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.1849 - tp: 4597.0000 - fp: 192.0000 - tn: 4927.0000 - fn: 524.0000 - accuracy: 0.9301 - precision: 0.9599 - recall: 0.8977 - auc: 0.9760 - prc: 0.9809"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1833 - tp: 7383.0000 - fp: 313.0000 - tn: 7837.0000 - fn: 851.0000 - accuracy: 0.9290 - precision: 0.9593 - recall: 0.8966 - auc: 0.9766 - prc: 0.9813"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1823 - tp: 10141.0000 - fp: 427.0000 - tn: 10817.0000 - fn: 1143.0000 - accuracy: 0.9303 - precision: 0.9596 - recall: 0.8987 - auc: 0.9768 - prc: 0.9815"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1834 - tp: 12933.0000 - fp: 545.0000 - tn: 13724.0000 - fn: 1470.0000 - accuracy: 0.9297 - precision: 0.9596 - recall: 0.8979 - auc: 0.9764 - prc: 0.9812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1836 - tp: 15645.0000 - fp: 673.0000 - tn: 16707.0000 - fn: 1791.0000 - accuracy: 0.9292 - precision: 0.9588 - recall: 0.8973 - auc: 0.9763 - prc: 0.9810"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1844 - tp: 18359.0000 - fp: 784.0000 - tn: 19701.0000 - fn: 2116.0000 - accuracy: 0.9292 - precision: 0.9590 - recall: 0.8967 - auc: 0.9760 - prc: 0.9808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.1844 - tp: 18359.0000 - fp: 784.0000 - tn: 19701.0000 - fn: 2116.0000 - accuracy: 0.9292 - precision: 0.9590 - recall: 0.8967 - auc: 0.9760 - prc: 0.9808 - val_loss: 0.1085 - val_tp: 59.0000 - val_fp: 615.0000 - val_tn: 44885.0000 - val_fn: 10.0000 - val_accuracy: 0.9863 - val_precision: 0.0875 - val_recall: 0.8551 - val_auc: 0.9681 - val_prc: 0.6725\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1846 - tp: 889.0000 - fp: 42.0000 - tn: 1008.0000 - fn: 109.0000 - accuracy: 0.9263 - precision: 0.9549 - recall: 0.8908 - auc: 0.9746 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.1875 - tp: 4555.0000 - fp: 220.0000 - tn: 4931.0000 - fn: 534.0000 - accuracy: 0.9264 - precision: 0.9539 - recall: 0.8951 - auc: 0.9745 - 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\b\b\b\r",
      " 7/20 [=========>....................] - ETA: 0s - loss: 0.1862 - tp: 6439.0000 - fp: 313.0000 - tn: 6841.0000 - fn: 743.0000 - accuracy: 0.9263 - precision: 0.9536 - recall: 0.8965 - auc: 0.9751 - prc: 0.9803"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1886 - tp: 8291.0000 - fp: 410.0000 - tn: 8777.0000 - fn: 954.0000 - accuracy: 0.9260 - precision: 0.9529 - recall: 0.8968 - auc: 0.9751 - prc: 0.9801"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1875 - tp: 10136.0000 - fp: 495.0000 - tn: 10733.0000 - fn: 1164.0000 - accuracy: 0.9264 - precision: 0.9534 - recall: 0.8970 - auc: 0.9751 - prc: 0.9802"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1860 - tp: 11901.0000 - fp: 565.0000 - tn: 12789.0000 - fn: 1369.0000 - accuracy: 0.9274 - precision: 0.9547 - recall: 0.8968 - auc: 0.9755 - prc: 0.9804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1843 - tp: 13732.0000 - fp: 647.0000 - tn: 14767.0000 - fn: 1574.0000 - accuracy: 0.9277 - precision: 0.9550 - recall: 0.8972 - auc: 0.9761 - prc: 0.9807"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1840 - tp: 16514.0000 - fp: 769.0000 - tn: 17690.0000 - fn: 1891.0000 - accuracy: 0.9278 - precision: 0.9555 - recall: 0.8973 - auc: 0.9760 - prc: 0.9808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1838 - tp: 18334.0000 - fp: 835.0000 - tn: 19677.0000 - fn: 2114.0000 - accuracy: 0.9280 - precision: 0.9564 - recall: 0.8966 - auc: 0.9760 - prc: 0.9808 - val_loss: 0.1054 - val_tp: 59.0000 - val_fp: 605.0000 - val_tn: 44895.0000 - val_fn: 10.0000 - val_accuracy: 0.9865 - val_precision: 0.0889 - val_recall: 0.8551 - val_auc: 0.9672 - val_prc: 0.6727\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 26/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1743 - tp: 918.0000 - fp: 34.0000 - tn: 986.0000 - fn: 110.0000 - accuracy: 0.9297 - precision: 0.9643 - recall: 0.8930 - auc: 0.9786 - 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\r",
      " 5/20 [======>.......................] - ETA: 0s - loss: 0.1803 - tp: 4576.0000 - fp: 204.0000 - tn: 4918.0000 - fn: 542.0000 - accuracy: 0.9271 - precision: 0.9573 - recall: 0.8941 - auc: 0.9771 - prc: 0.9817"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1806 - tp: 7315.0000 - fp: 334.0000 - tn: 7879.0000 - fn: 856.0000 - accuracy: 0.9274 - precision: 0.9563 - recall: 0.8952 - auc: 0.9772 - prc: 0.9816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1808 - tp: 10062.0000 - fp: 442.0000 - tn: 10841.0000 - fn: 1183.0000 - accuracy: 0.9279 - precision: 0.9579 - recall: 0.8948 - auc: 0.9773 - prc: 0.9816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1822 - tp: 12867.0000 - fp: 574.0000 - tn: 13731.0000 - fn: 1500.0000 - accuracy: 0.9277 - precision: 0.9573 - recall: 0.8956 - auc: 0.9771 - prc: 0.9814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1823 - tp: 15585.0000 - fp: 680.0000 - tn: 16723.0000 - fn: 1828.0000 - accuracy: 0.9280 - precision: 0.9582 - recall: 0.8950 - auc: 0.9771 - prc: 0.9814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1815 - tp: 18355.0000 - fp: 786.0000 - tn: 19667.0000 - fn: 2152.0000 - accuracy: 0.9283 - precision: 0.9589 - recall: 0.8951 - auc: 0.9772 - prc: 0.9816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 27ms/step - loss: 0.1815 - tp: 18355.0000 - fp: 786.0000 - tn: 19667.0000 - fn: 2152.0000 - accuracy: 0.9283 - precision: 0.9589 - recall: 0.8951 - auc: 0.9772 - prc: 0.9816 - val_loss: 0.1022 - val_tp: 59.0000 - val_fp: 594.0000 - val_tn: 44906.0000 - val_fn: 10.0000 - val_accuracy: 0.9867 - val_precision: 0.0904 - val_recall: 0.8551 - val_auc: 0.9676 - val_prc: 0.6633\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 27/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1782 - tp: 942.0000 - fp: 31.0000 - tn: 981.0000 - fn: 94.0000 - accuracy: 0.9390 - precision: 0.9681 - recall: 0.9093 - auc: 0.9778 - prc: 0.9827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1760 - tp: 4681.0000 - fp: 186.0000 - tn: 4861.0000 - fn: 512.0000 - accuracy: 0.9318 - precision: 0.9618 - recall: 0.9014 - auc: 0.9786 - 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\r",
      " 8/20 [===========>..................] - ETA: 0s - loss: 0.1777 - tp: 7386.0000 - fp: 305.0000 - tn: 7865.0000 - fn: 828.0000 - accuracy: 0.9308 - precision: 0.9603 - recall: 0.8992 - auc: 0.9781 - prc: 0.9824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1789 - tp: 10180.0000 - fp: 419.0000 - tn: 10779.0000 - fn: 1150.0000 - accuracy: 0.9304 - precision: 0.9605 - recall: 0.8985 - auc: 0.9778 - prc: 0.9823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1784 - tp: 11999.0000 - fp: 481.0000 - tn: 12780.0000 - fn: 1364.0000 - accuracy: 0.9307 - precision: 0.9615 - recall: 0.8979 - auc: 0.9779 - prc: 0.9823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1781 - tp: 13884.0000 - fp: 555.0000 - tn: 14714.0000 - fn: 1567.0000 - accuracy: 0.9309 - precision: 0.9616 - recall: 0.8986 - auc: 0.9780 - prc: 0.9823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1777 - tp: 15741.0000 - fp: 620.0000 - tn: 16683.0000 - fn: 1772.0000 - accuracy: 0.9313 - precision: 0.9621 - recall: 0.8988 - auc: 0.9780 - prc: 0.9824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1777 - tp: 18485.0000 - fp: 719.0000 - tn: 19678.0000 - fn: 2078.0000 - accuracy: 0.9317 - precision: 0.9626 - recall: 0.8989 - auc: 0.9780 - prc: 0.9824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1777 - tp: 18485.0000 - fp: 719.0000 - tn: 19678.0000 - fn: 2078.0000 - accuracy: 0.9317 - precision: 0.9626 - recall: 0.8989 - auc: 0.9780 - prc: 0.9824 - val_loss: 0.0995 - val_tp: 59.0000 - val_fp: 581.0000 - val_tn: 44919.0000 - val_fn: 10.0000 - val_accuracy: 0.9870 - val_precision: 0.0922 - val_recall: 0.8551 - val_auc: 0.9661 - val_prc: 0.6658\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 1/20 [>.............................] - ETA: 0s - loss: 0.1781 - tp: 902.0000 - fp: 39.0000 - tn: 994.0000 - fn: 113.0000 - accuracy: 0.9258 - precision: 0.9586 - recall: 0.8887 - auc: 0.9794 - prc: 0.9824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1782 - tp: 4453.0000 - fp: 200.0000 - tn: 5087.0000 - fn: 500.0000 - accuracy: 0.9316 - precision: 0.9570 - recall: 0.8991 - auc: 0.9780 - prc: 0.9808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1767 - tp: 7168.0000 - fp: 287.0000 - tn: 8118.0000 - fn: 811.0000 - accuracy: 0.9330 - precision: 0.9615 - recall: 0.8984 - auc: 0.9782 - prc: 0.9814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1752 - tp: 9962.0000 - fp: 409.0000 - tn: 11046.0000 - fn: 1111.0000 - accuracy: 0.9325 - precision: 0.9606 - recall: 0.8997 - auc: 0.9787 - prc: 0.9822"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1745 - tp: 12681.0000 - fp: 506.0000 - tn: 14084.0000 - fn: 1401.0000 - accuracy: 0.9335 - precision: 0.9616 - recall: 0.9005 - auc: 0.9789 - prc: 0.9823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1753 - tp: 15424.0000 - fp: 626.0000 - tn: 17037.0000 - fn: 1729.0000 - accuracy: 0.9324 - precision: 0.9610 - recall: 0.8992 - auc: 0.9786 - prc: 0.9822"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1745 - tp: 18219.0000 - fp: 729.0000 - tn: 19987.0000 - fn: 2025.0000 - accuracy: 0.9328 - precision: 0.9615 - recall: 0.9000 - auc: 0.9789 - prc: 0.9825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restoring model weights from the end of the best epoch: 18.\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\r",
      "20/20 [==============================] - 1s 27ms/step - loss: 0.1745 - tp: 18219.0000 - fp: 729.0000 - tn: 19987.0000 - fn: 2025.0000 - accuracy: 0.9328 - precision: 0.9615 - recall: 0.9000 - auc: 0.9789 - prc: 0.9825 - val_loss: 0.0967 - val_tp: 59.0000 - val_fp: 569.0000 - val_tn: 44931.0000 - val_fn: 10.0000 - val_accuracy: 0.9873 - val_precision: 0.0939 - val_recall: 0.8551 - val_auc: 0.9667 - val_prc: 0.6659\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28: 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": [
    "### トレーニング履歴を再確認する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:21.139931Z",
     "iopub.status.busy": "2022-12-14T23:08:21.139545Z",
     "iopub.status.idle": "2022-12-14T23:08:21.706020Z",
     "shell.execute_reply": "2022-12-14T23:08:21.705331Z"
    },
    "id": "FMycrpJwn39w"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### メトリクスを評価する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:21.710248Z",
     "iopub.status.busy": "2022-12-14T23:08:21.709757Z",
     "iopub.status.idle": "2022-12-14T23:08:22.126494Z",
     "shell.execute_reply": "2022-12-14T23:08:22.125768Z"
    },
    "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",
      "39/90 [============>.................] - 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",
      "80/90 [=========================>....] - 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: 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",
      "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": "2022-12-14T23:08:22.130248Z",
     "iopub.status.busy": "2022-12-14T23:08:22.129638Z",
     "iopub.status.idle": "2022-12-14T23:08:22.868733Z",
     "shell.execute_reply": "2022-12-14T23:08:22.868060Z"
    },
    "id": "FO0mMOYUDWFk"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss :  0.13150924444198608\n",
      "tp :  91.0\n",
      "fp :  728.0\n",
      "tn :  56133.0\n",
      "fn :  10.0\n",
      "accuracy :  0.9870439767837524\n",
      "precision :  0.1111111119389534\n",
      "recall :  0.9009901285171509\n",
      "auc :  0.9749700427055359\n",
      "prc :  0.7914559841156006\n",
      "\n",
      "Legitimate Transactions Detected (True Negatives):  56133\n",
      "Legitimate Transactions Incorrectly Detected (False Positives):  728\n",
      "Fraudulent Transactions Missed (False Negatives):  10\n",
      "Fraudulent Transactions Detected (True Positives):  91\n",
      "Total Fraudulent Transactions:  101\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### ROC をプロットする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:22.872256Z",
     "iopub.status.busy": "2022-12-14T23:08:22.871737Z",
     "iopub.status.idle": "2022-12-14T23:08:23.206647Z",
     "shell.execute_reply": "2022-12-14T23:08:23.205947Z"
    },
    "id": "fye_CiuYrZ1U"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": [
    "### AUPRC をプロットする\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:08:23.210957Z",
     "iopub.status.busy": "2022-12-14T23:08:23.210438Z",
     "iopub.status.idle": "2022-12-14T23:08:23.605575Z",
     "shell.execute_reply": "2022-12-14T23:08:23.604868Z"
    },
    "id": "wgWXQ8aeOhCZ"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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])\r\n",
    "plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\r\n",
    "\r\n",
    "plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\r\n",
    "plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\r\n",
    "\r\n",
    "plot_prc(\"Train Resampled\", train_labels, train_predictions_resampled, color=colors[2])\r\n",
    "plot_prc(\"Test Resampled\", test_labels, test_predictions_resampled, color=colors[2], linestyle='--')\r\n",
    "plt.legend(loc='lower right');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3o3f0ywl8uqW"
   },
   "source": [
    "## このチュートリアルを問題に応用する\n",
    "\n",
    "不均衡データの分類は、学習できるサンプルが非常に少ないため、本質的に難しい作業です。常に最初にデータから始め、できるだけ多くのサンプルを収集するよう最善を尽くし、モデルがマイノリティクラスを最大限に活用するのに適切な特徴はどれかを十分に検討する必要があります。ある時点では、モデルがなかなか改善せず望む結果をうまく生成できないことがあるので、問題のコンテキストおよび異なるタイプのエラー間のトレードオフを考慮することが重要です。"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
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