{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zwBCE43Cv3PH"
   },
   "source": [
    "##### Copyright 2019 The TensorFlow Authors.\n",
    "\n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:27.200431Z",
     "iopub.status.busy": "2022-12-14T20:52:27.200189Z",
     "iopub.status.idle": "2022-12-14T20:52:27.204257Z",
     "shell.execute_reply": "2022-12-14T20:52:27.203667Z"
    },
    "id": "fOad0I2cv569"
   },
   "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": "YQB7yiF6v9GR"
   },
   "source": [
    "# 팬더 DataFrame 로드하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Oqa952X4wQKK"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td><a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/load_data/pandas_dataframe\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\">TensorFlow.org에서 보기</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs-l10n/blob/master/site/ko/tutorials/load_data/pandas_dataframe.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\">Google Colab에서 실행하기</a></td>\n",
    "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/docs-l10n/blob/master/site/ko/tutorials/load_data/pandas_dataframe.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\">GitHub에서소스 보기</a></td>\n",
    "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/docs-l10n/site/ko/tutorials/load_data/pandas_dataframe.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\">노트북 다운로드하기</a></td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UmyEaf4Awl2v"
   },
   "source": [
    "이 튜토리얼에서는 <a href=\"https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html\" class=\"external\">pandas DataFrames</a>를 TensorFlow에 로드하는 방법의 예를 보여줍니다.\n",
    "\n",
    "UCI Machine Learning Repository에서 제공하는 작은 <a href=\"https://archive.ics.uci.edu/ml/datasets/heart+Disease\" class=\"external\">심장 질환 데이터세트</a>를 사용합니다. CSV에는 수백 개의 행이 있습니다. 각 행은 환자를 설명하고 각 열은 속성을 설명합니다. 이 정보를 사용하여 환자에게 심장병이 있는지 여부를 예측합니다. 이것은 이진 분류 작업에 해당합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iiyC7HkqxlUD"
   },
   "source": [
    "## pandas를 사용하여 데이터 읽기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:27.208356Z",
     "iopub.status.busy": "2022-12-14T20:52:27.207724Z",
     "iopub.status.idle": "2022-12-14T20:52:29.358256Z",
     "shell.execute_reply": "2022-12-14T20:52:29.357385Z"
    },
    "id": "5IoRbCA2n0_V"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-14 20:52:28.492546: 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 20:52:28.492656: 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 20:52:28.492666: 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 pandas as pd\n",
    "import tensorflow as tf\n",
    "\n",
    "SHUFFLE_BUFFER = 500\n",
    "BATCH_SIZE = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-2kBGy_pxn47"
   },
   "source": [
    "심장 질환 데이터세트가 포함된 CSV 파일 다운로드:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.362989Z",
     "iopub.status.busy": "2022-12-14T20:52:29.362119Z",
     "iopub.status.idle": "2022-12-14T20:52:29.414258Z",
     "shell.execute_reply": "2022-12-14T20:52:29.413551Z"
    },
    "id": "VS4w2LePn9g3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/download.tensorflow.org/data/heart.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 8192/13273 [=================>............] - 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\b\b\b\b\b\b\r",
      "13273/13273 [==============================] - 0s 0us/step\n"
     ]
    }
   ],
   "source": [
    "csv_file = tf.keras.utils.get_file('heart.csv', 'https://storage.googleapis.com/download.tensorflow.org/data/heart.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6BXRPD2-xtQ1"
   },
   "source": [
    "팬더를 사용하여 CSV 파일 읽기:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.418097Z",
     "iopub.status.busy": "2022-12-14T20:52:29.417573Z",
     "iopub.status.idle": "2022-12-14T20:52:29.424472Z",
     "shell.execute_reply": "2022-12-14T20:52:29.423868Z"
    },
    "id": "UEfJ8TcMpe-2"
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(csv_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4K873P-Pp8c7"
   },
   "source": [
    "데이터는 다음과 같습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.428097Z",
     "iopub.status.busy": "2022-12-14T20:52:29.427583Z",
     "iopub.status.idle": "2022-12-14T20:52:29.441963Z",
     "shell.execute_reply": "2022-12-14T20:52:29.441286Z"
    },
    "id": "8FkK6QIRpjd4"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>fixed</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>160</td>\n",
       "      <td>286</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>229</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>129</td>\n",
       "      <td>1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>reversible</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   1       145   233    1        2      150      0      2.3      3   \n",
       "1   67    1   4       160   286    0        2      108      1      1.5      2   \n",
       "2   67    1   4       120   229    0        2      129      1      2.6      2   \n",
       "3   37    1   3       130   250    0        0      187      0      3.5      3   \n",
       "4   41    0   2       130   204    0        2      172      0      1.4      1   \n",
       "\n",
       "   ca        thal  target  \n",
       "0   0       fixed       0  \n",
       "1   3      normal       1  \n",
       "2   2  reversible       0  \n",
       "3   0      normal       0  \n",
       "4   0      normal       0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.445259Z",
     "iopub.status.busy": "2022-12-14T20:52:29.444969Z",
     "iopub.status.idle": "2022-12-14T20:52:29.450463Z",
     "shell.execute_reply": "2022-12-14T20:52:29.449824Z"
    },
    "id": "_MOAKz654CT5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age           int64\n",
       "sex           int64\n",
       "cp            int64\n",
       "trestbps      int64\n",
       "chol          int64\n",
       "fbs           int64\n",
       "restecg       int64\n",
       "thalach       int64\n",
       "exang         int64\n",
       "oldpeak     float64\n",
       "slope         int64\n",
       "ca            int64\n",
       "thal         object\n",
       "target        int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jVyGjKvnqGlb"
   },
   "source": [
    "`target` 열에 포함된 레이블을 예측하는 모델을 빌드합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.453695Z",
     "iopub.status.busy": "2022-12-14T20:52:29.453164Z",
     "iopub.status.idle": "2022-12-14T20:52:29.456740Z",
     "shell.execute_reply": "2022-12-14T20:52:29.456122Z"
    },
    "id": "2wwhILm1ycSp"
   },
   "outputs": [],
   "source": [
    "target = df.pop('target')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vFGv9fgjDeao"
   },
   "source": [
    "## 배열로서의 DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xNxJ41MafiB-"
   },
   "source": [
    "데이터에 균일한 데이터 유형 또는 `dtype`이 있는 경우 NumPy 배열을 사용할 수 있는 모든 곳에서 pandas DataFrame을 사용할 수 있습니다. 이렇게 될 수 있는 이유는 `pandas.DataFrame` 클래스가 `__array__` 프로토콜을 지원하고 TensorFlow의 `tf.convert_to_tensor` 함수가 이 프로토콜을 지원하는 객체를 허용하기 때문입니다.\n",
    "\n",
    "데이터세트에서 숫자 특성을 가져옵니다(지금은 범주형 특성을 건너뜀)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.460094Z",
     "iopub.status.busy": "2022-12-14T20:52:29.459601Z",
     "iopub.status.idle": "2022-12-14T20:52:29.468842Z",
     "shell.execute_reply": "2022-12-14T20:52:29.468263Z"
    },
    "id": "b9VlFGAie3K0"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>thalach</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>oldpeak</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>150</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>67</td>\n",
       "      <td>108</td>\n",
       "      <td>160</td>\n",
       "      <td>286</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>67</td>\n",
       "      <td>129</td>\n",
       "      <td>120</td>\n",
       "      <td>229</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>187</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41</td>\n",
       "      <td>172</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  thalach  trestbps  chol  oldpeak\n",
       "0   63      150       145   233      2.3\n",
       "1   67      108       160   286      1.5\n",
       "2   67      129       120   229      2.6\n",
       "3   37      187       130   250      3.5\n",
       "4   41      172       130   204      1.4"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_feature_names = ['age', 'thalach', 'trestbps',  'chol', 'oldpeak']\n",
    "numeric_features = df[numeric_feature_names]\n",
    "numeric_features.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Xe1CMRvSpR_R"
   },
   "source": [
    "DataFrame은 `DataFrame.values` 속성 또는 `numpy.array(df)`를 사용하여 NumPy 배열로 변환할 수 있습니다. 텐서로 변환하려면 `tf.convert_to_tensor`를 사용하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:29.472071Z",
     "iopub.status.busy": "2022-12-14T20:52:29.471580Z",
     "iopub.status.idle": "2022-12-14T20:52:33.186844Z",
     "shell.execute_reply": "2022-12-14T20:52:33.186052Z"
    },
    "id": "OVv6Nwc9oDBU"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(303, 5), dtype=float64, numpy=\n",
       "array([[ 63. , 150. , 145. , 233. ,   2.3],\n",
       "       [ 67. , 108. , 160. , 286. ,   1.5],\n",
       "       [ 67. , 129. , 120. , 229. ,   2.6],\n",
       "       ...,\n",
       "       [ 65. , 127. , 135. , 254. ,   2.8],\n",
       "       [ 48. , 150. , 130. , 256. ,   0. ],\n",
       "       [ 63. , 154. , 150. , 407. ,   4. ]])>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.convert_to_tensor(numeric_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7iRYvoTrr1_G"
   },
   "source": [
    "일반적으로 `tf.convert_to_tensor`를 사용하여 객체를 텐서로 변환할 수 있는 경우 `tf.Tensor`를 전달할 수 있는 곳이면 어디든지 이를 전달할 수 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RVF7_Z-Mp-qD"
   },
   "source": [
    "### Model.fit과 함께 사용하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Vqkc9gIapQNu"
   },
   "source": [
    "단일 텐서로 해석되는 DataFrame은 `Model.fit` 메서드에 대한 인수로 직접 사용할 수 있습니다.\n",
    "\n",
    "다음은 데이터세트의 수치적 특성에 대한 모델 훈련의 예입니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u8M3oYHZgH_t"
   },
   "source": [
    "첫 단계는 입력 범위를 정규화하는 것입니다. 이를 위해 `tf.keras.layers.Normalization` 레이어를 사용합니다.\n",
    "\n",
    "레이어를 실행하기 전에 해당 평균과 표준편차를 설정하려면 `Normalization.adapt` 메서드를 호출해야 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:33.190991Z",
     "iopub.status.busy": "2022-12-14T20:52:33.190391Z",
     "iopub.status.idle": "2022-12-14T20:52:33.565088Z",
     "shell.execute_reply": "2022-12-14T20:52:33.564170Z"
    },
    "id": "88XTmyEdgkJn"
   },
   "outputs": [],
   "source": [
    "normalizer = tf.keras.layers.Normalization(axis=-1)\n",
    "normalizer.adapt(numeric_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_D7JqUtnYCnb"
   },
   "source": [
    "DataFrame의 처음 세 행에서 레이어를 호출하여 이 레이어의 출력 예를 시각화합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:33.569771Z",
     "iopub.status.busy": "2022-12-14T20:52:33.569203Z",
     "iopub.status.idle": "2022-12-14T20:52:33.583335Z",
     "shell.execute_reply": "2022-12-14T20:52:33.582568Z"
    },
    "id": "jOwzIG-DhB0y"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(3, 5), dtype=float32, numpy=\n",
       "array([[ 0.93383914,  0.03480718,  0.74578077, -0.26008663,  1.0680453 ],\n",
       "       [ 1.3782105 , -1.7806165 ,  1.5923285 ,  0.7573877 ,  0.38022864],\n",
       "       [ 1.3782105 , -0.87290466, -0.6651321 , -0.33687714,  1.3259765 ]],\n",
       "      dtype=float32)>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalizer(numeric_features.iloc[:3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KWKcuVZJh-HY"
   },
   "source": [
    "정규화 레이어를 단순 모델의 첫 번째 레이어로 사용합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:33.587187Z",
     "iopub.status.busy": "2022-12-14T20:52:33.586633Z",
     "iopub.status.idle": "2022-12-14T20:52:33.591154Z",
     "shell.execute_reply": "2022-12-14T20:52:33.590425Z"
    },
    "id": "lu-bni-nh6mX"
   },
   "outputs": [],
   "source": [
    "def get_basic_model():\n",
    "  model = tf.keras.Sequential([\n",
    "    normalizer,\n",
    "    tf.keras.layers.Dense(10, activation='relu'),\n",
    "    tf.keras.layers.Dense(10, activation='relu'),\n",
    "    tf.keras.layers.Dense(1)\n",
    "  ])\n",
    "\n",
    "  model.compile(optimizer='adam',\n",
    "                loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
    "                metrics=['accuracy'])\n",
    "  return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ntGi6ngYitob"
   },
   "source": [
    "DataFrame을 `Model.fit`에 `x` 인수로 전달하면 Keras는 DataFrame을 NumPy 배열인 것처럼 취급합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:33.594774Z",
     "iopub.status.busy": "2022-12-14T20:52:33.594071Z",
     "iopub.status.idle": "2022-12-14T20:52:41.626853Z",
     "shell.execute_reply": "2022-12-14T20:52:41.626002Z"
    },
    "id": "XMjM-eddiNNT"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4:10 - loss: 0.7045 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 0s - loss: 0.6487 - accuracy: 0.6579  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 0s - loss: 0.6372 - accuracy: 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\r",
      " 56/152 [==========>...................] - ETA: 0s - loss: 0.6322 - accuracy: 0.6696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/152 [=============>................] - ETA: 0s - loss: 0.6155 - accuracy: 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\r",
      " 94/152 [=================>............] - ETA: 0s - loss: 0.6063 - accuracy: 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\r",
      "113/152 [=====================>........] - ETA: 0s - loss: 0.5861 - accuracy: 0.7257"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "132/152 [=========================>....] - ETA: 0s - loss: 0.5763 - accuracy: 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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.5785 - accuracy: 0.7252"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 2s 3ms/step - loss: 0.5785 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4086 - accuracy: 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\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.4878 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/152 [======>.......................] - ETA: 0s - loss: 0.5363 - accuracy: 0.7308"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.5355 - accuracy: 0.7241"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/152 [==============>...............] - ETA: 0s - loss: 0.5293 - accuracy: 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\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.5373 - accuracy: 0.7083"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/152 [=====================>........] - ETA: 0s - loss: 0.5372 - accuracy: 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\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.5262 - accuracy: 0.7148"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.5209 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.7512 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 0s - loss: 0.4361 - accuracy: 0.7632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/152 [======>.......................] - ETA: 0s - loss: 0.4645 - accuracy: 0.7368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/152 [==========>...................] - ETA: 0s - loss: 0.4865 - accuracy: 0.7281"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4899 - accuracy: 0.7261"
     ]
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    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4899 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/15\n"
     ]
    },
    {
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     "output_type": "stream",
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      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.9754 - accuracy: 0.0000e+00"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4907 - accuracy: 0.7239"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4697 - accuracy: 0.7360\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.0053 - accuracy: 0.0000e+00"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4576 - accuracy: 0.7558\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.0219 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.5172 - accuracy: 0.6750"
     ]
    },
    {
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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\r",
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    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4501 - accuracy: 0.7657\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.3338 - accuracy: 0.5000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4455 - accuracy: 0.7624\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.5176 - accuracy: 0.5000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.4334 - accuracy: 0.7865"
     ]
    },
    {
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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\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4222 - accuracy: 0.7783"
     ]
    },
    {
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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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4624 - accuracy: 0.7612"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4413 - accuracy: 0.7789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4290 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.4262 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.4370 - accuracy: 0.7845"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 95/152 [=================>............] - ETA: 0s - loss: 0.4473 - accuracy: 0.7526"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4363 - accuracy: 0.7707"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4380 - accuracy: 0.7822"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4380 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4376 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.4837 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 59/152 [==========>...................] - ETA: 0s - loss: 0.4182 - accuracy: 0.7881"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4347 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.0088 - accuracy: 1.0000"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.3182 - accuracy: 0.8000"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/152 [==================>...........] - ETA: 0s - loss: 0.3946 - accuracy: 0.8247"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/152 [=====================>........] - ETA: 0s - loss: 0.3962 - accuracy: 0.7974"
     ]
    },
    {
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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\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.4194 - accuracy: 0.7889"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4339 - accuracy: 0.7855\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.2200 - accuracy: 1.0000"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.3124 - accuracy: 0.8750"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.4320 - accuracy: 0.7845"
     ]
    },
    {
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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\r",
      " 77/152 [==============>...............] - ETA: 0s - loss: 0.4238 - accuracy: 0.7727"
     ]
    },
    {
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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\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.4308 - accuracy: 0.7812"
     ]
    },
    {
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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\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4453 - accuracy: 0.7739"
     ]
    },
    {
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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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4295 - accuracy: 0.7873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4300 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.5697 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      " 21/152 [===>..........................] - ETA: 0s - loss: 0.4663 - accuracy: 0.7619"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 60/152 [==========>...................] - ETA: 0s - loss: 0.4600 - accuracy: 0.7833"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 98/152 [==================>...........] - ETA: 0s - loss: 0.4225 - accuracy: 0.8112"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4299 - accuracy: 0.7888\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.2066 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4362 - accuracy: 0.7873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4276 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.6814 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 0s - loss: 0.6308 - accuracy: 0.7368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 0s - loss: 0.5222 - accuracy: 0.8108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/152 [==========>...................] - ETA: 0s - loss: 0.5014 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 75/152 [=============>................] - ETA: 0s - loss: 0.4519 - accuracy: 0.7800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/152 [=================>............] - ETA: 0s - loss: 0.4332 - accuracy: 0.7872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/152 [=====================>........] - ETA: 0s - loss: 0.4281 - accuracy: 0.7920"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "132/152 [=========================>....] - ETA: 0s - loss: 0.4210 - accuracy: 0.7917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4261 - accuracy: 0.7914"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4249 - accuracy: 0.7921\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f517c35cb80>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = get_basic_model()\n",
    "model.fit(numeric_features, target, epochs=15, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EjtQbsRPEoJT"
   },
   "source": [
    "### tf.data와 함께 사용하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nSjV5gy3EsVv"
   },
   "source": [
    "`tf.data` 변환을 균일한 `dtype`의 DataFrame에 적용하려는 경우 `Dataset.from_tensor_slices` 메서드는 DataFrame의 행을 반복하는 데이터세트를 생성합니다. 각 행은 처음에 값으로 구성된 벡터입니다. 모델을 훈련시키려면 `(inputs, labels)` 쌍이 필요하므로 `(features, labels)`을 전달하면 `Dataset.from_tensor_slices`가 필요한 슬라이스 쌍을 반환합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:41.630877Z",
     "iopub.status.busy": "2022-12-14T20:52:41.630237Z",
     "iopub.status.idle": "2022-12-14T20:52:41.653314Z",
     "shell.execute_reply": "2022-12-14T20:52:41.652611Z"
    },
    "id": "FCphpgdRGikx"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(<tf.Tensor: shape=(5,), dtype=float64, numpy=array([ 63. , 150. , 145. , 233. ,   2.3])>, <tf.Tensor: shape=(), dtype=int64, numpy=0>)\n",
      "(<tf.Tensor: shape=(5,), dtype=float64, numpy=array([ 67. , 108. , 160. , 286. ,   1.5])>, <tf.Tensor: shape=(), dtype=int64, numpy=1>)\n",
      "(<tf.Tensor: shape=(5,), dtype=float64, numpy=array([ 67. , 129. , 120. , 229. ,   2.6])>, <tf.Tensor: shape=(), dtype=int64, numpy=0>)\n"
     ]
    }
   ],
   "source": [
    "numeric_dataset = tf.data.Dataset.from_tensor_slices((numeric_features, target))\n",
    "\n",
    "for row in numeric_dataset.take(3):\n",
    "  print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:41.657103Z",
     "iopub.status.busy": "2022-12-14T20:52:41.656470Z",
     "iopub.status.idle": "2022-12-14T20:52:48.946074Z",
     "shell.execute_reply": "2022-12-14T20:52:48.945118Z"
    },
    "id": "lStkN86gEkCe"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 2:41 - loss: 0.5778 - accuracy: 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\r",
      " 19/152 [==>...........................] - ETA: 0s - loss: 0.5947 - accuracy: 0.8421  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/152 [======>.......................] - ETA: 0s - loss: 0.6001 - accuracy: 0.7237"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.6158 - accuracy: 0.6897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/152 [==============>...............] - ETA: 0s - loss: 0.6081 - accuracy: 0.7078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.5895 - accuracy: 0.7188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/152 [=====================>........] - ETA: 0s - loss: 0.5826 - accuracy: 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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.5749 - accuracy: 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\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.5687 - accuracy: 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\r",
      "152/152 [==============================] - 1s 3ms/step - loss: 0.5687 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.5996 - accuracy: 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\r",
      " 21/152 [===>..........................] - ETA: 0s - loss: 0.5153 - accuracy: 0.7619    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/152 [=======>......................] - ETA: 0s - loss: 0.5127 - accuracy: 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\r",
      " 61/152 [===========>..................] - ETA: 0s - loss: 0.4868 - accuracy: 0.7623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/152 [==============>...............] - ETA: 0s - loss: 0.4689 - accuracy: 0.7716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/152 [==================>...........] - ETA: 0s - loss: 0.5003 - accuracy: 0.7525"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "120/152 [======================>.......] - ETA: 0s - loss: 0.5071 - accuracy: 0.7417"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/152 [==========================>...] - ETA: 0s - loss: 0.5025 - accuracy: 0.7464"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.5081 - accuracy: 0.7261\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Epoch 3/15\n"
     ]
    },
    {
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     "output_type": "stream",
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      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4834 - accuracy: 1.0000"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/152 [==================>...........] - ETA: 0s - loss: 0.5096 - accuracy: 0.7041"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4860 - accuracy: 0.7294\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.3604 - accuracy: 1.0000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.5601 - accuracy: 0.6750"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4799 - accuracy: 0.7243"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4721 - accuracy: 0.7360\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.6085 - accuracy: 0.0000e+00"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4655 - accuracy: 0.7327\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4226 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4573 - accuracy: 0.7426\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Epoch 7/15\n"
     ]
    },
    {
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     "output_type": "stream",
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      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.2694 - accuracy: 0.5000"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4521 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4513 - accuracy: 0.7459\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.0791 - accuracy: 1.0000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 0s - loss: 0.4895 - accuracy: 0.6750"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.4562 - accuracy: 0.7328"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/152 [==================>...........] - ETA: 0s - loss: 0.4660 - accuracy: 0.7449"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4464 - accuracy: 0.7591\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4891 - accuracy: 0.5000"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 99/152 [==================>...........] - ETA: 0s - loss: 0.4374 - accuracy: 0.7727"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4425 - accuracy: 0.7591\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.3461 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4385 - accuracy: 0.7756\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.2994 - accuracy: 1.0000"
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4358 - accuracy: 0.7789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.5924 - accuracy: 0.5000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/152 [===>..........................] - ETA: 0s - loss: 0.4312 - accuracy: 0.7619"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4344 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.0446 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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    },
    {
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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\r",
      " 98/152 [==================>...........] - ETA: 0s - loss: 0.4122 - accuracy: 0.8163"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4332 - accuracy: 0.7855\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/15\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 1.4755 - accuracy: 0.5000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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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\r",
      " 78/152 [==============>...............] - ETA: 0s - loss: 0.3707 - accuracy: 0.8269"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/152 [==================>...........] - ETA: 0s - loss: 0.3977 - accuracy: 0.8144"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "117/152 [======================>.......] - ETA: 0s - loss: 0.4150 - accuracy: 0.7991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4365 - accuracy: 0.7757"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4284 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.8215 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 0s - loss: 0.5017 - accuracy: 0.8158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/152 [======>.......................] - ETA: 0s - loss: 0.4538 - accuracy: 0.8205"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/152 [==========>...................] - ETA: 0s - loss: 0.4246 - accuracy: 0.7881"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/152 [==============>...............] - ETA: 0s - loss: 0.4117 - accuracy: 0.7975"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 99/152 [==================>...........] - ETA: 0s - loss: 0.4151 - accuracy: 0.7828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/152 [======================>.......] - ETA: 0s - loss: 0.4303 - accuracy: 0.7731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "138/152 [==========================>...] - ETA: 0s - loss: 0.4239 - accuracy: 0.7862"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 0s 3ms/step - loss: 0.4273 - accuracy: 0.7822\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f517c06e040>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_batches = numeric_dataset.shuffle(1000).batch(BATCH_SIZE)\n",
    "\n",
    "model = get_basic_model()\n",
    "model.fit(numeric_batches, epochs=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NRASs9IIESWQ"
   },
   "source": [
    "## DataFrame을 사전으로 사용"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NQcp7kiPF8TP"
   },
   "source": [
    "이기종 데이터를 다루기 시작하면 DataFrame을 더 이상 단일 배열인 것처럼 취급할 수 없습니다. TensorFlow 텐서는 모든 요소의 `dtype`이 같을 것을 요구합니다.\n",
    "\n",
    "따라서 이 경우, 이를 각 열에 균일한 `dtype`이 있는 열 사전으로 취급해야 합니다. DataFrame은 배열 사전과 매우 유사하므로 일반적으로 DataFrame을 Python dict로 캐스팅하기만 하면 됩니다. 많은 중요한 TensorFlow API가 배열의 (중첩) 사전을 입력으로 지원합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9y5UMKL8bury"
   },
   "source": [
    "`tf.data` 입력 파이프라인은 이것을 아주 잘 처리합니다. 모든 `tf.data` 연산이 사전과 튜플을 자동으로 처리합니다. 따라서 DataFrame에서 사전-예제의 데이터세트를 만들려면 `Dataset.from_tensor_slices`로 슬라이싱하기 전에 dict로 캐스팅하면 됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:48.950555Z",
     "iopub.status.busy": "2022-12-14T20:52:48.949787Z",
     "iopub.status.idle": "2022-12-14T20:52:48.963003Z",
     "shell.execute_reply": "2022-12-14T20:52:48.962066Z"
    },
    "id": "U3QDo-jwHYXc"
   },
   "outputs": [],
   "source": [
    "numeric_dict_ds = tf.data.Dataset.from_tensor_slices((dict(numeric_features), target))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yyEERK9ldIi_"
   },
   "source": [
    "다음은 해당 데이터세트의 처음 세 가지 예입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:48.966643Z",
     "iopub.status.busy": "2022-12-14T20:52:48.966343Z",
     "iopub.status.idle": "2022-12-14T20:52:48.981028Z",
     "shell.execute_reply": "2022-12-14T20:52:48.980401Z"
    },
    "id": "q0tDwk0VdH6D"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "({'age': <tf.Tensor: shape=(), dtype=int64, numpy=63>, 'thalach': <tf.Tensor: shape=(), dtype=int64, numpy=150>, 'trestbps': <tf.Tensor: shape=(), dtype=int64, numpy=145>, 'chol': <tf.Tensor: shape=(), dtype=int64, numpy=233>, 'oldpeak': <tf.Tensor: shape=(), dtype=float64, numpy=2.3>}, <tf.Tensor: shape=(), dtype=int64, numpy=0>)\n",
      "({'age': <tf.Tensor: shape=(), dtype=int64, numpy=67>, 'thalach': <tf.Tensor: shape=(), dtype=int64, numpy=108>, 'trestbps': <tf.Tensor: shape=(), dtype=int64, numpy=160>, 'chol': <tf.Tensor: shape=(), dtype=int64, numpy=286>, 'oldpeak': <tf.Tensor: shape=(), dtype=float64, numpy=1.5>}, <tf.Tensor: shape=(), dtype=int64, numpy=1>)\n",
      "({'age': <tf.Tensor: shape=(), dtype=int64, numpy=67>, 'thalach': <tf.Tensor: shape=(), dtype=int64, numpy=129>, 'trestbps': <tf.Tensor: shape=(), dtype=int64, numpy=120>, 'chol': <tf.Tensor: shape=(), dtype=int64, numpy=229>, 'oldpeak': <tf.Tensor: shape=(), dtype=float64, numpy=2.6>}, <tf.Tensor: shape=(), dtype=int64, numpy=0>)\n"
     ]
    }
   ],
   "source": [
    "for row in numeric_dict_ds.take(3):\n",
    "  print(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DEAM6HAFxlMy"
   },
   "source": [
    "### Keras를 사용한 사전"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dnoyoWLWx07i"
   },
   "source": [
    "일반적으로 Keras 모델과 레이어는 단일 입력 텐서를 기대하지만 이러한 클래스는 사전, 튜플 및 텐서의 중첩 구조를 허용하고 반환할 수 있습니다. 이러한 구조를 \"중첩\"이라고 합니다(자세한 내용은 `tf.nest` 모듈 참조).\n",
    "\n",
    "사전을 입력으로 받아들이는 Keras 모델을 작성할 수 있는 동등한 효과의 두 가지 방법이 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5xUTrm0apDTr"
   },
   "source": [
    "#### 1. 모델-서브 클래스 스타일\n",
    "\n",
    "`tf.keras.Model`(또는 `tf.keras.Layer`)의 서브 클래스를 작성합니다. 입력을 직접 처리하고 출력을 생성합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:48.985072Z",
     "iopub.status.busy": "2022-12-14T20:52:48.984461Z",
     "iopub.status.idle": "2022-12-14T20:52:48.988637Z",
     "shell.execute_reply": "2022-12-14T20:52:48.987960Z"
    },
    "id": "Zc3HV99CFRWL"
   },
   "outputs": [],
   "source": [
    "  def stack_dict(inputs, fun=tf.stack):\n",
    "    values = []\n",
    "    for key in sorted(inputs.keys()):\n",
    "      values.append(tf.cast(inputs[key], tf.float32))\n",
    "\n",
    "    return fun(values, axis=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:48.992112Z",
     "iopub.status.busy": "2022-12-14T20:52:48.991548Z",
     "iopub.status.idle": "2022-12-14T20:52:49.217869Z",
     "shell.execute_reply": "2022-12-14T20:52:49.217110Z"
    },
    "id": "Rz4Cg6WpzNzi"
   },
   "outputs": [],
   "source": [
    "#@title\n",
    "class MyModel(tf.keras.Model):\n",
    "  def __init__(self):\n",
    "    # Create all the internal layers in init.\n",
    "    super().__init__(self)\n",
    "\n",
    "    self.normalizer = tf.keras.layers.Normalization(axis=-1)\n",
    "\n",
    "    self.seq = tf.keras.Sequential([\n",
    "      self.normalizer,\n",
    "      tf.keras.layers.Dense(10, activation='relu'),\n",
    "      tf.keras.layers.Dense(10, activation='relu'),\n",
    "      tf.keras.layers.Dense(1)\n",
    "    ])\n",
    "\n",
    "  def adapt(self, inputs):\n",
    "    # Stack the inputs and `adapt` the normalization layer.\n",
    "    inputs = stack_dict(inputs)\n",
    "    self.normalizer.adapt(inputs)\n",
    "\n",
    "  def call(self, inputs):\n",
    "    # Stack the inputs\n",
    "    inputs = stack_dict(inputs)\n",
    "    # Run them through all the layers.\n",
    "    result = self.seq(inputs)\n",
    "\n",
    "    return result\n",
    "\n",
    "model = MyModel()\n",
    "\n",
    "model.adapt(dict(numeric_features))\n",
    "\n",
    "model.compile(optimizer='adam',\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
    "              metrics=['accuracy'],\n",
    "              run_eagerly=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hMLXNEDF_tu2"
   },
   "source": [
    "이 모델은 학습을 위해 열 사전 또는 사전-요소의 데이터세트를 허용할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:52:49.222476Z",
     "iopub.status.busy": "2022-12-14T20:52:49.221966Z",
     "iopub.status.idle": "2022-12-14T20:53:09.983656Z",
     "shell.execute_reply": "2022-12-14T20:53:09.982762Z"
    },
    "id": "v3xEjtHY8gZG"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:5 out of the last 5 calls to <function _BaseOptimizer._update_step_xla at 0x7f514c655280> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:6 out of the last 6 calls to <function _BaseOptimizer._update_step_xla at 0x7f514c655280> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 1:55 - loss: 0.7522 - accuracy: 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\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.5488 - accuracy: 0.8333  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/152 [..............................] - ETA: 3s - loss: 0.5972 - accuracy: 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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.6729 - accuracy: 0.5714"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.6846 - accuracy: 0.5556"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/152 [=>............................] - ETA: 3s - loss: 0.6288 - accuracy: 0.5909"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.6117 - accuracy: 0.6154"
     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.6278 - accuracy: 0.5333"
     ]
    },
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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\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.6257 - accuracy: 0.5833"
     ]
    },
    {
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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\r",
      " 20/152 [==>...........................] - ETA: 3s - loss: 0.6241 - accuracy: 0.6250"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.6281 - accuracy: 0.6591"
     ]
    },
    {
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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\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.6291 - accuracy: 0.6458"
     ]
    },
    {
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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\r",
      " 26/152 [====>.........................] - ETA: 3s - loss: 0.6340 - accuracy: 0.6154"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/152 [====>.........................] - ETA: 3s - loss: 0.6134 - accuracy: 0.6429"
     ]
    },
    {
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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\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.6090 - accuracy: 0.6667"
     ]
    },
    {
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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\r",
      " 32/152 [=====>........................] - ETA: 3s - loss: 0.6105 - accuracy: 0.6875"
     ]
    },
    {
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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\r",
      " 34/152 [=====>........................] - ETA: 3s - loss: 0.6154 - accuracy: 0.6912"
     ]
    },
    {
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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\r",
      " 36/152 [======>.......................] - ETA: 3s - loss: 0.6076 - accuracy: 0.6944"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/152 [======>.......................] - ETA: 2s - loss: 0.6121 - accuracy: 0.6842"
     ]
    },
    {
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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\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.6056 - accuracy: 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\r",
      " 42/152 [=======>......................] - ETA: 2s - loss: 0.5997 - accuracy: 0.6905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/152 [=======>......................] - ETA: 2s - loss: 0.5980 - accuracy: 0.7045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/152 [========>.....................] - ETA: 2s - loss: 0.5927 - accuracy: 0.7021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.5896 - accuracy: 0.7041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/152 [=========>....................] - ETA: 2s - loss: 0.6000 - accuracy: 0.6863"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/152 [=========>....................] - ETA: 2s - loss: 0.6023 - accuracy: 0.6887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.6066 - accuracy: 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\r",
      " 57/152 [==========>...................] - ETA: 2s - loss: 0.6035 - accuracy: 0.6579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/152 [==========>...................] - ETA: 2s - loss: 0.6031 - accuracy: 0.6610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.6081 - accuracy: 0.6557"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/152 [===========>..................] - ETA: 2s - loss: 0.6097 - accuracy: 0.6508"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 65/152 [===========>..................] - ETA: 2s - loss: 0.6202 - accuracy: 0.6462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/152 [============>.................] - ETA: 2s - loss: 0.6193 - accuracy: 0.6343"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/152 [============>.................] - ETA: 2s - loss: 0.6173 - accuracy: 0.6377"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/152 [=============>................] - ETA: 2s - loss: 0.6156 - accuracy: 0.6479"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.5658 - accuracy: 0.7310"
     ]
    },
    {
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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\r",
      "147/152 [============================>.] - ETA: 0s - loss: 0.5662 - accuracy: 0.7279"
     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.5651 - accuracy: 0.7282"
     ]
    },
    {
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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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.5648 - accuracy: 0.7285"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.5658 - accuracy: 0.7294"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 5s 26ms/step - loss: 0.5658 - accuracy: 0.7294\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.4592 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.7472 - accuracy: 0.6667"
     ]
    },
    {
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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\r",
      "  5/152 [..............................] - ETA: 3s - loss: 0.7007 - accuracy: 0.6000"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.5961 - accuracy: 0.6429"
     ]
    },
    {
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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\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.5468 - accuracy: 0.7222"
     ]
    },
    {
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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\r",
      " 11/152 [=>............................] - ETA: 3s - loss: 0.5517 - accuracy: 0.6818"
     ]
    },
    {
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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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.5604 - accuracy: 0.6923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.5325 - accuracy: 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\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.5467 - accuracy: 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\r",
      " 20/152 [==>...........................] - ETA: 3s - loss: 0.5197 - accuracy: 0.7000"
     ]
    },
    {
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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\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.5300 - accuracy: 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\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.5263 - accuracy: 0.7292"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/152 [====>.........................] - ETA: 3s - loss: 0.5237 - accuracy: 0.7037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.5228 - accuracy: 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\r",
      " 32/152 [=====>........................] - ETA: 3s - loss: 0.5290 - accuracy: 0.7188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/152 [=====>........................] - ETA: 2s - loss: 0.5114 - accuracy: 0.7286"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.5183 - accuracy: 0.7297"
     ]
    },
    {
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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\r",
      " 39/152 [======>.......................] - ETA: 2s - loss: 0.5265 - accuracy: 0.7179"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/152 [=======>......................] - ETA: 2s - loss: 0.5307 - accuracy: 0.7195"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.5180 - accuracy: 0.7326"
     ]
    },
    {
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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\r",
      " 45/152 [=======>......................] - ETA: 2s - loss: 0.5142 - accuracy: 0.7333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/152 [========>.....................] - ETA: 2s - loss: 0.5185 - accuracy: 0.7340"
     ]
    },
    {
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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\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.5327 - accuracy: 0.7245"
     ]
    },
    {
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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\r",
      " 51/152 [=========>....................] - ETA: 2s - loss: 0.5313 - accuracy: 0.7353"
     ]
    },
    {
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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\r",
      " 53/152 [=========>....................] - ETA: 2s - loss: 0.5214 - accuracy: 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\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.5274 - accuracy: 0.7545"
     ]
    },
    {
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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\r",
      " 57/152 [==========>...................] - ETA: 2s - loss: 0.5357 - accuracy: 0.7456"
     ]
    },
    {
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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\r",
      " 59/152 [==========>...................] - ETA: 2s - loss: 0.5277 - accuracy: 0.7542"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 99/152 [==================>...........] - ETA: 1s - loss: 0.4945 - accuracy: 0.7626"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "105/152 [===================>..........] - ETA: 1s - loss: 0.4853 - accuracy: 0.7667"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "111/152 [====================>.........] - ETA: 1s - loss: 0.4952 - accuracy: 0.7658"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.4970 - accuracy: 0.7598"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "129/152 [========================>.....] - ETA: 0s - loss: 0.5072 - accuracy: 0.7481"
     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/152 [========================>.....] - ETA: 0s - loss: 0.5062 - accuracy: 0.7443"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.5058 - accuracy: 0.7444"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.5045 - accuracy: 0.7407"
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.5057 - accuracy: 0.7409"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.5045 - accuracy: 0.7410"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "141/152 [==========================>...] - ETA: 0s - loss: 0.5063 - accuracy: 0.7376"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.5045 - accuracy: 0.7378"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.5120 - accuracy: 0.7276"
     ]
    },
    {
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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\r",
      "147/152 [============================>.] - ETA: 0s - loss: 0.5077 - accuracy: 0.7313"
     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.5063 - accuracy: 0.7315"
     ]
    },
    {
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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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.5061 - accuracy: 0.7285"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 26ms/step - loss: 0.5072 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.3840 - accuracy: 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\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.3256 - accuracy: 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\r",
      "  5/152 [..............................] - ETA: 3s - loss: 0.3683 - accuracy: 0.9000"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.3801 - accuracy: 0.9286"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.5215 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/152 [=>............................] - ETA: 3s - loss: 0.5024 - accuracy: 0.8182"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/152 [=>............................] - ETA: 3s - loss: 0.5528 - accuracy: 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\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.5378 - accuracy: 0.7188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.5258 - accuracy: 0.7222"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 3s - loss: 0.5523 - accuracy: 0.7250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.5300 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.5310 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/152 [====>.........................] - ETA: 3s - loss: 0.5071 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/152 [====>.........................] - ETA: 3s - loss: 0.5181 - accuracy: 0.7679"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.5134 - accuracy: 0.7667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/152 [=====>........................] - ETA: 3s - loss: 0.5264 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 34/152 [=====>........................] - ETA: 3s - loss: 0.5631 - accuracy: 0.7206"
     ]
    },
    {
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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\r",
      " 36/152 [======>.......................] - ETA: 2s - loss: 0.5517 - accuracy: 0.7361"
     ]
    },
    {
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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\r",
      " 38/152 [======>.......................] - ETA: 2s - loss: 0.5420 - accuracy: 0.7368"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "111/152 [====================>.........] - ETA: 1s - loss: 0.5226 - accuracy: 0.7117"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/152 [=====================>........] - ETA: 1s - loss: 0.5218 - accuracy: 0.7080"
     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.5179 - accuracy: 0.7087"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/152 [======================>.......] - ETA: 0s - loss: 0.5113 - accuracy: 0.7101"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.5110 - accuracy: 0.7025"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "123/152 [=======================>......] - ETA: 0s - loss: 0.5079 - accuracy: 0.7073"
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.5052 - accuracy: 0.7143"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.5003 - accuracy: 0.7185"
     ]
    },
    {
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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\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.5006 - accuracy: 0.7190"
     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4968 - accuracy: 0.7230"
     ]
    },
    {
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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\r",
      "141/152 [==========================>...] - ETA: 0s - loss: 0.4928 - accuracy: 0.7234"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.4916 - accuracy: 0.7238"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4909 - accuracy: 0.7241"
     ]
    },
    {
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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\r",
      "147/152 [============================>.] - ETA: 0s - loss: 0.4920 - accuracy: 0.7245"
     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.4878 - accuracy: 0.7282"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4842 - accuracy: 0.7285"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 26ms/step - loss: 0.4829 - accuracy: 0.7294\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.5805 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.3890 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/152 [..............................] - ETA: 3s - loss: 0.3256 - accuracy: 0.9000"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.3916 - accuracy: 0.8571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.3588 - accuracy: 0.8889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/152 [=>............................] - ETA: 3s - loss: 0.3972 - accuracy: 0.8182"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4272 - accuracy: 0.8077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.4860 - accuracy: 0.7333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/152 [==>...........................] - ETA: 3s - loss: 0.4711 - accuracy: 0.7353"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4508 - accuracy: 0.7632"
     ]
    },
    {
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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\r",
      " 21/152 [===>..........................] - ETA: 3s - loss: 0.4599 - accuracy: 0.7381"
     ]
    },
    {
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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\r",
      " 23/152 [===>..........................] - ETA: 3s - loss: 0.4552 - accuracy: 0.7391"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.4811 - accuracy: 0.6923"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 56/152 [==========>...................] - ETA: 2s - loss: 0.4813 - accuracy: 0.7054"
     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.4782 - accuracy: 0.7069"
     ]
    },
    {
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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\r",
      " 60/152 [==========>...................] - ETA: 2s - loss: 0.4682 - accuracy: 0.7167"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/152 [================>.............] - ETA: 1s - loss: 0.4400 - accuracy: 0.7582"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 99/152 [==================>...........] - ETA: 1s - loss: 0.4603 - accuracy: 0.7576"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/152 [==================>...........] - ETA: 1s - loss: 0.4665 - accuracy: 0.7475"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.4650 - accuracy: 0.7524"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "111/152 [====================>.........] - ETA: 1s - loss: 0.4700 - accuracy: 0.7432"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/152 [=====================>........] - ETA: 1s - loss: 0.4715 - accuracy: 0.7389"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4811 - accuracy: 0.7348"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.4757 - accuracy: 0.7308"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.4724 - accuracy: 0.7349"
     ]
    },
    {
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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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4704 - accuracy: 0.7351"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 4s 26ms/step - loss: 0.4704 - accuracy: 0.7327\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.6623 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.4190 - accuracy: 0.8333"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  5/152 [..............................] - ETA: 3s - loss: 0.3170 - accuracy: 0.9000"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.3406 - accuracy: 0.7857"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.3169 - accuracy: 0.8333"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 11/152 [=>............................] - ETA: 3s - loss: 0.3172 - accuracy: 0.8182"
     ]
    },
    {
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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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.3260 - accuracy: 0.8462"
     ]
    },
    {
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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\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.3715 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
      " 17/152 [==>...........................] - ETA: 3s - loss: 0.3888 - accuracy: 0.7941"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4133 - accuracy: 0.7632"
     ]
    },
    {
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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\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.3814 - accuracy: 0.7727"
     ]
    },
    {
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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\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.3938 - accuracy: 0.7708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/152 [====>.........................] - ETA: 3s - loss: 0.3919 - accuracy: 0.7885"
     ]
    },
    {
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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\r",
      " 28/152 [====>.........................] - ETA: 3s - loss: 0.3815 - accuracy: 0.8036"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.3738 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
      " 32/152 [=====>........................] - ETA: 3s - loss: 0.3650 - accuracy: 0.7969"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 3s - loss: 0.3662 - accuracy: 0.7941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/152 [======>.......................] - ETA: 3s - loss: 0.3642 - accuracy: 0.7917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/152 [======>.......................] - ETA: 2s - loss: 0.3673 - accuracy: 0.8026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/152 [=======>......................] - ETA: 2s - loss: 0.3903 - accuracy: 0.7927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.3927 - accuracy: 0.7791"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/152 [=======>......................] - ETA: 2s - loss: 0.3995 - accuracy: 0.7667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/152 [========>.....................] - ETA: 2s - loss: 0.4068 - accuracy: 0.7553"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.4161 - accuracy: 0.7449"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/152 [=========>....................] - ETA: 2s - loss: 0.4186 - accuracy: 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\r",
      " 53/152 [=========>....................] - ETA: 2s - loss: 0.4368 - accuracy: 0.7358"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.4368 - accuracy: 0.7364"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/152 [==========>...................] - ETA: 2s - loss: 0.4380 - accuracy: 0.7368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/152 [==========>...................] - ETA: 2s - loss: 0.4395 - accuracy: 0.7288"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.4404 - accuracy: 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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.4281 - accuracy: 0.7422"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/152 [==================>...........] - ETA: 1s - loss: 0.4570 - accuracy: 0.7398"
     ]
    },
    {
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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\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.4658 - accuracy: 0.7350"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/152 [==========================>...] - ETA: 0s - loss: 0.4584 - accuracy: 0.7607"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4580 - accuracy: 0.7606"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "144/152 [===========================>..] - ETA: 0s - loss: 0.4598 - accuracy: 0.7569"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/152 [===========================>..] - ETA: 0s - loss: 0.4612 - accuracy: 0.7534"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4564 - accuracy: 0.7568"
     ]
    },
    {
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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\r",
      "150/152 [============================>.] - ETA: 0s - loss: 0.4595 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4616 - accuracy: 0.7459"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 26ms/step - loss: 0.4616 - accuracy: 0.7459\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f517c0bc730>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(dict(numeric_features), target, epochs=5, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:09.987586Z",
     "iopub.status.busy": "2022-12-14T20:53:09.986993Z",
     "iopub.status.idle": "2022-12-14T20:53:27.399282Z",
     "shell.execute_reply": "2022-12-14T20:53:27.398451Z"
    },
    "id": "73wgiTaVAA2F"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.5197 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.6727 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.7118 - accuracy: 0.5714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.5687 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.5581 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.5103 - accuracy: 0.8125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4705 - accuracy: 0.7895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.4676 - accuracy: 0.7727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 2s - loss: 0.4788 - accuracy: 0.7800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/152 [====>.........................] - ETA: 2s - loss: 0.4994 - accuracy: 0.7679"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/152 [=====>........................] - ETA: 2s - loss: 0.5008 - accuracy: 0.7581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.5018 - accuracy: 0.7353"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.5213 - accuracy: 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\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.5150 - accuracy: 0.7375"
     ]
    },
    {
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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\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.4996 - accuracy: 0.7442"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/152 [========>.....................] - ETA: 2s - loss: 0.4841 - accuracy: 0.7609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.4627 - accuracy: 0.7755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.4698 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.4797 - accuracy: 0.7455"
     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.4708 - accuracy: 0.7414"
     ]
    },
    {
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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\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.4578 - accuracy: 0.7541"
     ]
    },
    {
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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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.4728 - accuracy: 0.7344"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 70/152 [============>.................] - ETA: 1s - loss: 0.4631 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 73/152 [=============>................] - ETA: 1s - loss: 0.4612 - accuracy: 0.7466"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/152 [================>.............] - ETA: 1s - loss: 0.4781 - accuracy: 0.7386"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/152 [================>.............] - ETA: 1s - loss: 0.4706 - accuracy: 0.7473"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/152 [=================>............] - ETA: 1s - loss: 0.4737 - accuracy: 0.7500"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/152 [==================>...........] - ETA: 1s - loss: 0.4692 - accuracy: 0.7474"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.4733 - accuracy: 0.7500"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.4685 - accuracy: 0.7524"
     ]
    },
    {
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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\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.4671 - accuracy: 0.7547"
     ]
    },
    {
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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\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.4708 - accuracy: 0.7523"
     ]
    },
    {
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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\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4653 - accuracy: 0.7589"
     ]
    },
    {
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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\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4642 - accuracy: 0.7609"
     ]
    },
    {
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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\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4694 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.4658 - accuracy: 0.7521"
     ]
    },
    {
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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\r",
      "124/152 [=======================>......] - ETA: 0s - loss: 0.4595 - accuracy: 0.7581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.4541 - accuracy: 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\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.4524 - accuracy: 0.7654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4549 - accuracy: 0.7632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4575 - accuracy: 0.7647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4537 - accuracy: 0.7662"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4574 - accuracy: 0.7570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4554 - accuracy: 0.7552"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4502 - accuracy: 0.7568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4578 - accuracy: 0.7550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 3s 23ms/step - loss: 0.4567 - accuracy: 0.7558\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.5472 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.2749 - accuracy: 0.8750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.2812 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.3097 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.3195 - accuracy: 0.8077"
     ]
    },
    {
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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\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.3502 - accuracy: 0.8125"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.4340 - accuracy: 0.7586"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.4285 - accuracy: 0.7812"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4259 - accuracy: 0.7522"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4246 - accuracy: 0.7542"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4396 - accuracy: 0.7519"
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4388 - accuracy: 0.7518"
     ]
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4459 - accuracy: 0.7500"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4535 - accuracy: 0.7448"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4529 - accuracy: 0.7466"
     ]
    },
    {
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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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4536 - accuracy: 0.7483"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 3s 23ms/step - loss: 0.4524 - accuracy: 0.7492\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.0552 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.2093 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.2074 - accuracy: 0.9286"
     ]
    },
    {
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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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.4575 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4741 - accuracy: 0.7308"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.4489 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4971 - accuracy: 0.7105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 2s - loss: 0.5271 - accuracy: 0.7045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 2s - loss: 0.5046 - accuracy: 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\r",
      " 28/152 [====>.........................] - ETA: 2s - loss: 0.4807 - accuracy: 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\r",
      " 31/152 [=====>........................] - ETA: 2s - loss: 0.4652 - accuracy: 0.7258"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.4649 - accuracy: 0.7206"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.4605 - accuracy: 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\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.4390 - accuracy: 0.7250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.4353 - accuracy: 0.7209"
     ]
    },
    {
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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\r",
      " 46/152 [========>.....................] - ETA: 2s - loss: 0.4265 - accuracy: 0.7283"
     ]
    },
    {
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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\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.4335 - accuracy: 0.7245"
     ]
    },
    {
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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\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.4106 - accuracy: 0.7404"
     ]
    },
    {
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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\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.4074 - accuracy: 0.7455"
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    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.3992 - accuracy: 0.7586"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.4158 - accuracy: 0.7541"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 64/152 [===========>..................] - ETA: 1s - loss: 0.4075 - accuracy: 0.7656"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/152 [=============>................] - ETA: 1s - loss: 0.4131 - accuracy: 0.7534"
     ]
    },
    {
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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\r",
      " 76/152 [==============>...............] - ETA: 1s - loss: 0.4114 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 79/152 [==============>...............] - ETA: 1s - loss: 0.4072 - accuracy: 0.7532"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/152 [===============>..............] - ETA: 1s - loss: 0.4038 - accuracy: 0.7561"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/152 [===============>..............] - ETA: 1s - loss: 0.4045 - accuracy: 0.7588"
     ]
    },
    {
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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\r",
      " 88/152 [================>.............] - ETA: 1s - loss: 0.4032 - accuracy: 0.7614"
     ]
    },
    {
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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\r",
      " 91/152 [================>.............] - ETA: 1s - loss: 0.4161 - accuracy: 0.7473"
     ]
    },
    {
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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\r",
      " 94/152 [=================>............] - ETA: 1s - loss: 0.4135 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 97/152 [==================>...........] - ETA: 1s - loss: 0.4258 - accuracy: 0.7423"
     ]
    },
    {
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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\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.4215 - accuracy: 0.7450"
     ]
    },
    {
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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\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.4255 - accuracy: 0.7476"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.4347 - accuracy: 0.7406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.4501 - accuracy: 0.7339"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4502 - accuracy: 0.7321"
     ]
    },
    {
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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\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4516 - accuracy: 0.7348"
     ]
    },
    {
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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\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4476 - accuracy: 0.7415"
     ]
    },
    {
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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\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.4492 - accuracy: 0.7397"
     ]
    },
    {
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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\r",
      "124/152 [=======================>......] - ETA: 0s - loss: 0.4602 - accuracy: 0.7379"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4558 - accuracy: 0.7481"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4522 - accuracy: 0.7518"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4504 - accuracy: 0.7535"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4438 - accuracy: 0.7586"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4461 - accuracy: 0.7601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4471 - accuracy: 0.7583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 3s 23ms/step - loss: 0.4482 - accuracy: 0.7591\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.1579 - accuracy: 1.0000"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.4306 - accuracy: 0.8750"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.4828 - accuracy: 0.8571"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.3848 - accuracy: 0.8750"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4551 - accuracy: 0.8158"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.4233 - accuracy: 0.8409"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.4320 - accuracy: 0.7941"
     ]
    },
    {
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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\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.4352 - accuracy: 0.7973"
     ]
    },
    {
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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\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.4193 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.4537 - accuracy: 0.7755"
     ]
    },
    {
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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\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.4589 - accuracy: 0.7692"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.4791 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.4851 - accuracy: 0.7422"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 79/152 [==============>...............] - ETA: 1s - loss: 0.4594 - accuracy: 0.7595"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.4585 - accuracy: 0.7650"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.4632 - accuracy: 0.7573"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.4628 - accuracy: 0.7547"
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.4623 - accuracy: 0.7569"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4651 - accuracy: 0.7545"
     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4616 - accuracy: 0.7522"
     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4528 - accuracy: 0.7585"
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/152 [=======================>......] - ETA: 0s - loss: 0.4510 - accuracy: 0.7621"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.4468 - accuracy: 0.7677"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.4579 - accuracy: 0.7654"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4610 - accuracy: 0.7632"
     ]
    },
    {
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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\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4580 - accuracy: 0.7647"
     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4533 - accuracy: 0.7662"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4497 - accuracy: 0.7676"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4522 - accuracy: 0.7655"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4469 - accuracy: 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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4462 - accuracy: 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\r",
      "152/152 [==============================] - 3s 23ms/step - loss: 0.4450 - accuracy: 0.7723\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 1.0701 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.3951 - accuracy: 0.8750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.3208 - accuracy: 0.9286"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.3613 - accuracy: 0.9000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.3227 - accuracy: 0.8846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.3046 - accuracy: 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\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.3497 - accuracy: 0.8421"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.3950 - accuracy: 0.8409"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 2s - loss: 0.3899 - accuracy: 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\r",
      " 28/152 [====>.........................] - ETA: 2s - loss: 0.3995 - accuracy: 0.8036"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/152 [=====>........................] - ETA: 2s - loss: 0.3839 - accuracy: 0.8065"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.3784 - accuracy: 0.7941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.3749 - accuracy: 0.8108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.4045 - accuracy: 0.7875"
     ]
    },
    {
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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\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.3820 - accuracy: 0.8017"
     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
      " 76/152 [==============>...............] - ETA: 1s - loss: 0.4163 - accuracy: 0.8092"
     ]
    },
    {
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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\r",
      " 79/152 [==============>...............] - ETA: 1s - loss: 0.4156 - accuracy: 0.7975"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 94/152 [=================>............] - ETA: 1s - loss: 0.4174 - accuracy: 0.7872"
     ]
    },
    {
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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\r",
      " 97/152 [==================>...........] - ETA: 1s - loss: 0.4206 - accuracy: 0.7887"
     ]
    },
    {
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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\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.4261 - accuracy: 0.7850"
     ]
    },
    {
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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\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.4329 - accuracy: 0.7864"
     ]
    },
    {
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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\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.4343 - accuracy: 0.7830"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4296 - accuracy: 0.7857"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4419 - accuracy: 0.7817"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4444 - accuracy: 0.7793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4434 - accuracy: 0.7838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4427 - accuracy: 0.7815"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 3s 23ms/step - loss: 0.4414 - accuracy: 0.7822\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f514c5d6c70>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_dict_batches = numeric_dict_ds.shuffle(SHUFFLE_BUFFER).batch(BATCH_SIZE)\n",
    "model.fit(numeric_dict_batches, epochs=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-xDB3HLZGzAb"
   },
   "source": [
    "다음은 처음 세 가지 예에 대한 예측입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:27.402766Z",
     "iopub.status.busy": "2022-12-14T20:53:27.402490Z",
     "iopub.status.idle": "2022-12-14T20:53:27.498046Z",
     "shell.execute_reply": "2022-12-14T20:53:27.497327Z"
    },
    "id": "xtolTQA-GpBW"
   },
   "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 37ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[[0.09959535]],\n",
       "\n",
       "       [[0.2687521 ]],\n",
       "\n",
       "       [[0.68996304]]], dtype=float32)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(dict(numeric_features.iloc[:3]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QIIdxIYm13Ik"
   },
   "source": [
    "#### 2. Keras의 기능적 스타일"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:27.502159Z",
     "iopub.status.busy": "2022-12-14T20:53:27.501478Z",
     "iopub.status.idle": "2022-12-14T20:53:27.511272Z",
     "shell.execute_reply": "2022-12-14T20:53:27.510573Z"
    },
    "id": "DG_bmO0sS_G5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'age': <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'age')>,\n",
       " 'thalach': <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'thalach')>,\n",
       " 'trestbps': <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'trestbps')>,\n",
       " 'chol': <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'chol')>,\n",
       " 'oldpeak': <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'oldpeak')>}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs = {}\n",
    "for name, column in numeric_features.items():\n",
    "  inputs[name] = tf.keras.Input(\n",
    "      shape=(1,), name=name, dtype=tf.float32)\n",
    "\n",
    "inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:27.514960Z",
     "iopub.status.busy": "2022-12-14T20:53:27.514275Z",
     "iopub.status.idle": "2022-12-14T20:53:27.768306Z",
     "shell.execute_reply": "2022-12-14T20:53:27.767450Z"
    },
    "id": "9iXU9oem12dL"
   },
   "outputs": [],
   "source": [
    "x = stack_dict(inputs, fun=tf.concat)\n",
    "\n",
    "normalizer = tf.keras.layers.Normalization(axis=-1)\n",
    "normalizer.adapt(stack_dict(dict(numeric_features)))\n",
    "\n",
    "x = normalizer(x)\n",
    "x = tf.keras.layers.Dense(10, activation='relu')(x)\n",
    "x = tf.keras.layers.Dense(10, activation='relu')(x)\n",
    "x = tf.keras.layers.Dense(1)(x)\n",
    "\n",
    "model = tf.keras.Model(inputs, x)\n",
    "\n",
    "model.compile(optimizer='adam',\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
    "              metrics=['accuracy'],\n",
    "              run_eagerly=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:27.772930Z",
     "iopub.status.busy": "2022-12-14T20:53:27.772219Z",
     "iopub.status.idle": "2022-12-14T20:53:28.031139Z",
     "shell.execute_reply": "2022-12-14T20:53:28.030104Z"
    },
    "id": "xrAxmuJrEwnf"
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(model, rankdir=\"LR\", show_shapes=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UYtoAOIzCFY1"
   },
   "source": [
    "모델 서브 클래스와 동일한 방식으로 기능적 모델을 훈련할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:28.035488Z",
     "iopub.status.busy": "2022-12-14T20:53:28.034845Z",
     "iopub.status.idle": "2022-12-14T20:53:46.668492Z",
     "shell.execute_reply": "2022-12-14T20:53:46.667769Z"
    },
    "id": "yAwjPq7I_ehX"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 1:46 - loss: 0.8923 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.7587 - accuracy: 0.7500  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.7375 - accuracy: 0.6429"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.7076 - accuracy: 0.6500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.7249 - accuracy: 0.6923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.7448 - accuracy: 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\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.7272 - accuracy: 0.7222"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/152 [==>...........................] - ETA: 3s - loss: 0.7232 - accuracy: 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\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.7195 - accuracy: 0.6818"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 3s - loss: 0.7166 - accuracy: 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\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.6731 - accuracy: 0.7244"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.6695 - accuracy: 0.7308"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.6682 - accuracy: 0.7331"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.6678 - accuracy: 0.7279"
     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.6685 - accuracy: 0.7230"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.6665 - accuracy: 0.7183"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.6649 - accuracy: 0.7207"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.6629 - accuracy: 0.7230"
     ]
    },
    {
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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\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.6602 - accuracy: 0.7285"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.6597 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.5899 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.5424 - accuracy: 0.8750"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.5722 - accuracy: 0.7857"
     ]
    },
    {
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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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.5932 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.5906 - accuracy: 0.6923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.5882 - accuracy: 0.7188"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.5887 - accuracy: 0.7105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 2s - loss: 0.5922 - accuracy: 0.7045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 2s - loss: 0.5892 - accuracy: 0.7083"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/152 [====>.........................] - ETA: 2s - loss: 0.5978 - accuracy: 0.7037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 2s - loss: 0.5975 - accuracy: 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\r",
      " 33/152 [=====>........................] - ETA: 2s - loss: 0.5990 - accuracy: 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\r",
      " 36/152 [======>.......................] - ETA: 2s - loss: 0.5905 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/152 [======>.......................] - ETA: 2s - loss: 0.5808 - accuracy: 0.7564"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/152 [=======>......................] - ETA: 2s - loss: 0.5817 - accuracy: 0.7619"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/152 [=======>......................] - ETA: 2s - loss: 0.5919 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/152 [========>.....................] - ETA: 2s - loss: 0.5919 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.5835 - accuracy: 0.7551"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.5811 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.5862 - accuracy: 0.7455"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.5804 - accuracy: 0.7414"
     ]
    },
    {
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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\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.5752 - accuracy: 0.7459"
     ]
    },
    {
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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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.5712 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 67/152 [============>.................] - ETA: 1s - loss: 0.5676 - accuracy: 0.7537"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/152 [==============>...............] - ETA: 1s - loss: 0.5761 - accuracy: 0.7468"
     ]
    },
    {
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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\r",
      " 82/152 [===============>..............] - ETA: 1s - loss: 0.5700 - accuracy: 0.7561"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/152 [===============>..............] - ETA: 1s - loss: 0.5753 - accuracy: 0.7412"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 88/152 [================>.............] - ETA: 1s - loss: 0.5722 - accuracy: 0.7500"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/152 [================>.............] - ETA: 1s - loss: 0.5691 - accuracy: 0.7473"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 94/152 [=================>............] - ETA: 1s - loss: 0.5695 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      " 97/152 [==================>...........] - ETA: 1s - loss: 0.5662 - accuracy: 0.7526"
     ]
    },
    {
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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\r",
      "100/152 [==================>...........] - ETA: 1s - loss: 0.5603 - accuracy: 0.7600"
     ]
    },
    {
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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\r",
      "103/152 [===================>..........] - ETA: 1s - loss: 0.5573 - accuracy: 0.7670"
     ]
    },
    {
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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\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.5535 - accuracy: 0.7689"
     ]
    },
    {
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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\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.5562 - accuracy: 0.7615"
     ]
    },
    {
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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\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.5560 - accuracy: 0.7634"
     ]
    },
    {
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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\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.5527 - accuracy: 0.7652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.5562 - accuracy: 0.7627"
     ]
    },
    {
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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\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.5508 - accuracy: 0.7686"
     ]
    },
    {
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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\r",
      "124/152 [=======================>......] - ETA: 0s - loss: 0.5500 - accuracy: 0.7661"
     ]
    },
    {
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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\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.5507 - accuracy: 0.7598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.5591 - accuracy: 0.7462"
     ]
    },
    {
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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\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.5563 - accuracy: 0.7519"
     ]
    },
    {
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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\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.5547 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.5524 - accuracy: 0.7518"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.5533 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.5507 - accuracy: 0.7517"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.5566 - accuracy: 0.7466"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.5550 - accuracy: 0.7483"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 23ms/step - loss: 0.5541 - accuracy: 0.7492\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.3662 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.5704 - accuracy: 0.6250"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.5928 - accuracy: 0.6429"
     ]
    },
    {
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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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.5667 - accuracy: 0.7000"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 2s - loss: 0.4983 - accuracy: 0.7500"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
      " 46/152 [========>.....................] - ETA: 2s - loss: 0.5365 - accuracy: 0.7174"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.5365 - accuracy: 0.7241"
     ]
    },
    {
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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\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.5257 - accuracy: 0.7377"
     ]
    },
    {
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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\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.5249 - accuracy: 0.7344"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 79/152 [==============>...............] - ETA: 1s - loss: 0.5092 - accuracy: 0.7468"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.4910 - accuracy: 0.7615"
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4938 - accuracy: 0.7589"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.5014 - accuracy: 0.7478"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.4904 - accuracy: 0.7559"
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4881 - accuracy: 0.7556"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4955 - accuracy: 0.7426"
     ]
    },
    {
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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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4916 - accuracy: 0.7446"
     ]
    },
    {
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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\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4891 - accuracy: 0.7465"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4885 - accuracy: 0.7517"
     ]
    },
    {
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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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4885 - accuracy: 0.7534"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4867 - accuracy: 0.7550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 23ms/step - loss: 0.4860 - accuracy: 0.7558\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.2242 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.4194 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.4611 - accuracy: 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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.4430 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4087 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.4306 - accuracy: 0.7812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4888 - accuracy: 0.7368"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.4736 - accuracy: 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\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.4525 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/152 [====>.........................] - ETA: 3s - loss: 0.4394 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 29/152 [====>.........................] - ETA: 2s - loss: 0.4281 - accuracy: 0.7759"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/152 [=====>........................] - ETA: 2s - loss: 0.4289 - accuracy: 0.7742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 33/152 [=====>........................] - ETA: 2s - loss: 0.4108 - accuracy: 0.7879"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/152 [======>.......................] - ETA: 2s - loss: 0.3994 - accuracy: 0.7917"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/152 [======>.......................] - ETA: 2s - loss: 0.3930 - accuracy: 0.7821"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/152 [=======>......................] - ETA: 2s - loss: 0.3908 - accuracy: 0.7857"
     ]
    },
    {
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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\r",
      " 45/152 [=======>......................] - ETA: 2s - loss: 0.4037 - accuracy: 0.7778"
     ]
    },
    {
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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\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/152 [===========================>..] - ETA: 0s - loss: 0.4530 - accuracy: 0.7568"
     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.4603 - accuracy: 0.7550"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4570 - accuracy: 0.7591"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.4570 - accuracy: 0.7591\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.5901 - accuracy: 0.5000"
     ]
    },
    {
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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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.6529 - accuracy: 0.7500"
     ]
    },
    {
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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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.6100 - accuracy: 0.7143"
     ]
    },
    {
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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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.4664 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4110 - accuracy: 0.8462"
     ]
    },
    {
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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\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.3717 - accuracy: 0.8438"
     ]
    },
    {
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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\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.3731 - accuracy: 0.7895"
     ]
    },
    {
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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\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.3791 - accuracy: 0.7727"
     ]
    },
    {
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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\r",
      " 25/152 [===>..........................] - ETA: 2s - loss: 0.3662 - accuracy: 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\r",
      " 28/152 [====>.........................] - ETA: 2s - loss: 0.3623 - accuracy: 0.8214"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 31/152 [=====>........................] - ETA: 2s - loss: 0.3754 - accuracy: 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\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.4289 - accuracy: 0.7647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 2s - loss: 0.4586 - accuracy: 0.7432"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/152 [======>.......................] - ETA: 2s - loss: 0.4544 - accuracy: 0.7625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.4622 - accuracy: 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\r",
      " 46/152 [========>.....................] - ETA: 2s - loss: 0.4482 - accuracy: 0.7717"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 2s - loss: 0.4466 - accuracy: 0.7755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/152 [=========>....................] - ETA: 2s - loss: 0.4531 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/152 [=========>....................] - ETA: 2s - loss: 0.4607 - accuracy: 0.7636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 2s - loss: 0.4547 - accuracy: 0.7672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 2s - loss: 0.4395 - accuracy: 0.7787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 64/152 [===========>..................] - ETA: 2s - loss: 0.4381 - accuracy: 0.7812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/152 [============>.................] - ETA: 2s - loss: 0.4413 - accuracy: 0.7836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/152 [============>.................] - ETA: 1s - loss: 0.4381 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/152 [=============>................] - ETA: 1s - loss: 0.4385 - accuracy: 0.7877"
     ]
    },
    {
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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\r",
      " 76/152 [==============>...............] - ETA: 1s - loss: 0.4401 - accuracy: 0.7829"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 86/152 [===============>..............] - ETA: 1s - loss: 0.4620 - accuracy: 0.7849"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/152 [==================>...........] - ETA: 1s - loss: 0.4464 - accuracy: 0.7857"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "101/152 [==================>...........] - ETA: 1s - loss: 0.4501 - accuracy: 0.7871"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/152 [===================>..........] - ETA: 1s - loss: 0.4513 - accuracy: 0.7837"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/152 [=====================>........] - ETA: 0s - loss: 0.4342 - accuracy: 0.7931"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "122/152 [=======================>......] - ETA: 0s - loss: 0.4476 - accuracy: 0.7787"
     ]
    },
    {
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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\r",
      "125/152 [=======================>......] - ETA: 0s - loss: 0.4597 - accuracy: 0.7680"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4485 - accuracy: 0.7761"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.4554 - accuracy: 0.7701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4530 - accuracy: 0.7698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4516 - accuracy: 0.7711"
     ]
    },
    {
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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\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4501 - accuracy: 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\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4450 - accuracy: 0.7736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4438 - accuracy: 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\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.4431 - accuracy: 0.7723\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f52f5244220>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(dict(numeric_features), target, epochs=5, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:53:46.672176Z",
     "iopub.status.busy": "2022-12-14T20:53:46.671617Z",
     "iopub.status.idle": "2022-12-14T20:54:05.252396Z",
     "shell.execute_reply": "2022-12-14T20:54:05.251678Z"
    },
    "id": "brwodxxVApO_"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.0798 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.1801 - accuracy: 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\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.3198 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.3114 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4364 - accuracy: 0.7308"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.4904 - accuracy: 0.6875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.4533 - accuracy: 0.7105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.4342 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 3s - loss: 0.4594 - accuracy: 0.7400"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "111/152 [====================>.........] - ETA: 1s - loss: 0.4166 - accuracy: 0.7703"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/152 [=====================>........] - ETA: 0s - loss: 0.4207 - accuracy: 0.7611"
     ]
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4170 - accuracy: 0.7652"
     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4237 - accuracy: 0.7669"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.4298 - accuracy: 0.7645"
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "123/152 [=======================>......] - ETA: 0s - loss: 0.4278 - accuracy: 0.7683"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "126/152 [=======================>......] - ETA: 0s - loss: 0.4242 - accuracy: 0.7698"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "129/152 [========================>.....] - ETA: 0s - loss: 0.4252 - accuracy: 0.7713"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "132/152 [=========================>....] - ETA: 0s - loss: 0.4199 - accuracy: 0.7727"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.4202 - accuracy: 0.7704"
     ]
    },
    {
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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\r",
      "138/152 [==========================>...] - ETA: 0s - loss: 0.4203 - accuracy: 0.7717"
     ]
    },
    {
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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\r",
      "141/152 [==========================>...] - ETA: 0s - loss: 0.4248 - accuracy: 0.7730"
     ]
    },
    {
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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\r",
      "144/152 [===========================>..] - ETA: 0s - loss: 0.4265 - accuracy: 0.7743"
     ]
    },
    {
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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\r",
      "147/152 [============================>.] - ETA: 0s - loss: 0.4253 - accuracy: 0.7755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "150/152 [============================>.] - ETA: 0s - loss: 0.4305 - accuracy: 0.7733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.4361 - accuracy: 0.7723\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.5966 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.3378 - accuracy: 0.6250    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.2997 - accuracy: 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\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.3018 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.3303 - accuracy: 0.7692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 16/152 [==>...........................] - ETA: 3s - loss: 0.3553 - accuracy: 0.7812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.3600 - accuracy: 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\r",
      " 21/152 [===>..........................] - ETA: 3s - loss: 0.3715 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.4431 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/152 [====>.........................] - ETA: 3s - loss: 0.4423 - accuracy: 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\r",
      " 30/152 [====>.........................] - ETA: 2s - loss: 0.4359 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 33/152 [=====>........................] - ETA: 2s - loss: 0.4332 - accuracy: 0.7727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/152 [======>.......................] - ETA: 2s - loss: 0.4270 - accuracy: 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\r",
      " 38/152 [======>.......................] - ETA: 2s - loss: 0.4193 - accuracy: 0.7895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/152 [=======>......................] - ETA: 2s - loss: 0.3959 - accuracy: 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\r",
      " 43/152 [=======>......................] - ETA: 2s - loss: 0.3812 - accuracy: 0.8140"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/152 [=======>......................] - ETA: 2s - loss: 0.4009 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "105/152 [===================>..........] - ETA: 1s - loss: 0.4111 - accuracy: 0.7857"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "125/152 [=======================>......] - ETA: 0s - loss: 0.4308 - accuracy: 0.7800"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "128/152 [========================>.....] - ETA: 0s - loss: 0.4336 - accuracy: 0.7812"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/152 [========================>.....] - ETA: 0s - loss: 0.4406 - accuracy: 0.7748"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4379 - accuracy: 0.7782"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "135/152 [=========================>....] - ETA: 0s - loss: 0.4415 - accuracy: 0.7741"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.4357 - accuracy: 0.7774"
     ]
    },
    {
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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\r",
      "140/152 [==========================>...] - ETA: 0s - loss: 0.4357 - accuracy: 0.7750"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.4371 - accuracy: 0.7762"
     ]
    },
    {
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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\r",
      "146/152 [===========================>..] - ETA: 0s - loss: 0.4362 - accuracy: 0.7740"
     ]
    },
    {
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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\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.4351 - accuracy: 0.7752"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4314 - accuracy: 0.7756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 25ms/step - loss: 0.4314 - accuracy: 0.7756\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3s - loss: 0.0543 - accuracy: 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\r",
      "  4/152 [..............................] - ETA: 3s - loss: 0.5172 - accuracy: 0.7500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/152 [>.............................] - ETA: 3s - loss: 0.4220 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 10/152 [>.............................] - ETA: 3s - loss: 0.4153 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 3s - loss: 0.4160 - accuracy: 0.8077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 15/152 [=>............................] - ETA: 3s - loss: 0.4188 - accuracy: 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\r",
      " 17/152 [==>...........................] - ETA: 3s - loss: 0.4177 - accuracy: 0.7941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/152 [==>...........................] - ETA: 3s - loss: 0.3950 - accuracy: 0.8158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/152 [===>..........................] - ETA: 3s - loss: 0.3707 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.3746 - accuracy: 0.8125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/152 [====>.........................] - ETA: 3s - loss: 0.4158 - accuracy: 0.7963"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.3938 - accuracy: 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\r",
      " 32/152 [=====>........................] - ETA: 2s - loss: 0.3840 - accuracy: 0.7969"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/152 [=====>........................] - ETA: 2s - loss: 0.3684 - accuracy: 0.8088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/152 [======>.......................] - ETA: 2s - loss: 0.3638 - accuracy: 0.8194"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 39/152 [======>.......................] - ETA: 2s - loss: 0.3520 - accuracy: 0.8205"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/152 [=======>......................] - ETA: 2s - loss: 0.3462 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 45/152 [=======>......................] - ETA: 2s - loss: 0.3672 - accuracy: 0.8222"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/152 [========>.....................] - ETA: 2s - loss: 0.3584 - accuracy: 0.8229"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/152 [=========>....................] - ETA: 2s - loss: 0.3684 - accuracy: 0.8235"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/152 [=========>....................] - ETA: 2s - loss: 0.3905 - accuracy: 0.8056"
     ]
    },
    {
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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\r",
      " 57/152 [==========>...................] - ETA: 2s - loss: 0.3980 - accuracy: 0.7982"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4431 - accuracy: 0.7724"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.4369 - accuracy: 0.7774"
     ]
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/152 [==========================>...] - ETA: 0s - loss: 0.4298 - accuracy: 0.7821"
     ]
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    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.4290 - accuracy: 0.7832"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4258 - accuracy: 0.7862"
     ]
    },
    {
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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\r",
      "147/152 [============================>.] - ETA: 0s - loss: 0.4292 - accuracy: 0.7823"
     ]
    },
    {
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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\r",
      "150/152 [============================>.] - ETA: 0s - loss: 0.4255 - accuracy: 0.7833"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 4s 25ms/step - loss: 0.4298 - accuracy: 0.7822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.1276 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.4202 - accuracy: 0.8333"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  6/152 [>.............................] - ETA: 3s - loss: 0.3407 - accuracy: 0.8333"
     ]
    },
    {
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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\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.3301 - accuracy: 0.8889"
     ]
    },
    {
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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\r",
      " 12/152 [=>............................] - ETA: 3s - loss: 0.3259 - accuracy: 0.8750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/152 [=>............................] - ETA: 3s - loss: 0.4021 - accuracy: 0.8571"
     ]
    },
    {
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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\r",
      " 17/152 [==>...........................] - ETA: 3s - loss: 0.3908 - accuracy: 0.8529"
     ]
    },
    {
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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\r",
      " 20/152 [==>...........................] - ETA: 3s - loss: 0.3890 - accuracy: 0.8500"
     ]
    },
    {
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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\r",
      " 22/152 [===>..........................] - ETA: 3s - loss: 0.4083 - accuracy: 0.8182"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.4091 - accuracy: 0.8125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/152 [====>.........................] - ETA: 3s - loss: 0.3930 - accuracy: 0.8077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/152 [====>.........................] - ETA: 3s - loss: 0.3832 - accuracy: 0.8036"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 30/152 [====>.........................] - ETA: 3s - loss: 0.4001 - accuracy: 0.7833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 32/152 [=====>........................] - ETA: 2s - loss: 0.3833 - accuracy: 0.7969"
     ]
    },
    {
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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\r",
      " 35/152 [=====>........................] - ETA: 2s - loss: 0.3714 - accuracy: 0.8143"
     ]
    },
    {
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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\r",
      " 38/152 [======>.......................] - ETA: 2s - loss: 0.3586 - accuracy: 0.8289"
     ]
    },
    {
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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\r",
      " 41/152 [=======>......................] - ETA: 2s - loss: 0.3472 - accuracy: 0.8415"
     ]
    },
    {
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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\r",
      " 44/152 [=======>......................] - ETA: 2s - loss: 0.3318 - accuracy: 0.8523"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/152 [========>.....................] - ETA: 2s - loss: 0.3429 - accuracy: 0.8511"
     ]
    },
    {
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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\r",
      " 50/152 [========>.....................] - ETA: 2s - loss: 0.4055 - accuracy: 0.8200"
     ]
    },
    {
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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\r",
      " 53/152 [=========>....................] - ETA: 2s - loss: 0.4186 - accuracy: 0.8113"
     ]
    },
    {
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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\r",
      " 56/152 [==========>...................] - ETA: 2s - loss: 0.4094 - accuracy: 0.8125"
     ]
    },
    {
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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\r",
      " 59/152 [==========>...................] - ETA: 2s - loss: 0.3995 - accuracy: 0.8220"
     ]
    },
    {
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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\r",
      " 62/152 [===========>..................] - ETA: 2s - loss: 0.3911 - accuracy: 0.8226"
     ]
    },
    {
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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\r",
      " 65/152 [===========>..................] - ETA: 2s - loss: 0.3848 - accuracy: 0.8231"
     ]
    },
    {
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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\r",
      " 68/152 [============>.................] - ETA: 2s - loss: 0.3817 - accuracy: 0.8235"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 71/152 [=============>................] - ETA: 1s - loss: 0.3810 - accuracy: 0.8310"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/152 [=============>................] - ETA: 1s - loss: 0.3969 - accuracy: 0.8243"
     ]
    },
    {
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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\r",
      " 77/152 [==============>...............] - ETA: 1s - loss: 0.3928 - accuracy: 0.8247"
     ]
    },
    {
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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\r",
      " 80/152 [==============>...............] - ETA: 1s - loss: 0.3975 - accuracy: 0.8188"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/152 [===============>..............] - ETA: 1s - loss: 0.3941 - accuracy: 0.8193"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 86/152 [===============>..............] - ETA: 1s - loss: 0.4006 - accuracy: 0.8081"
     ]
    },
    {
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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\r",
      " 89/152 [================>.............] - ETA: 1s - loss: 0.4000 - accuracy: 0.8090"
     ]
    },
    {
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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\r",
      " 92/152 [=================>............] - ETA: 1s - loss: 0.4048 - accuracy: 0.8043"
     ]
    },
    {
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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\r",
      " 95/152 [=================>............] - ETA: 1s - loss: 0.4114 - accuracy: 0.8000"
     ]
    },
    {
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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\r",
      " 98/152 [==================>...........] - ETA: 1s - loss: 0.4155 - accuracy: 0.7959"
     ]
    },
    {
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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\r",
      "101/152 [==================>...........] - ETA: 1s - loss: 0.4117 - accuracy: 0.7970"
     ]
    },
    {
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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\r",
      "104/152 [===================>..........] - ETA: 1s - loss: 0.4165 - accuracy: 0.7933"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/152 [====================>.........] - ETA: 1s - loss: 0.4299 - accuracy: 0.7897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/152 [====================>.........] - ETA: 1s - loss: 0.4225 - accuracy: 0.7955"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "113/152 [=====================>........] - ETA: 0s - loss: 0.4157 - accuracy: 0.7965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "116/152 [=====================>........] - ETA: 0s - loss: 0.4260 - accuracy: 0.7888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/152 [======================>.......] - ETA: 0s - loss: 0.4208 - accuracy: 0.7941"
     ]
    },
    {
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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\r",
      "122/152 [=======================>......] - ETA: 0s - loss: 0.4283 - accuracy: 0.7828"
     ]
    },
    {
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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\r",
      "125/152 [=======================>......] - ETA: 0s - loss: 0.4316 - accuracy: 0.7800"
     ]
    },
    {
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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\r",
      "128/152 [========================>.....] - ETA: 0s - loss: 0.4270 - accuracy: 0.7852"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/152 [========================>.....] - ETA: 0s - loss: 0.4263 - accuracy: 0.7863"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/152 [=========================>....] - ETA: 0s - loss: 0.4274 - accuracy: 0.7836"
     ]
    },
    {
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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\r",
      "137/152 [==========================>...] - ETA: 0s - loss: 0.4266 - accuracy: 0.7810"
     ]
    },
    {
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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\r",
      "140/152 [==========================>...] - ETA: 0s - loss: 0.4274 - accuracy: 0.7786"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.4217 - accuracy: 0.7832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/152 [===========================>..] - ETA: 0s - loss: 0.4224 - accuracy: 0.7842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/152 [============================>.] - ETA: 0s - loss: 0.4325 - accuracy: 0.7819"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.4268 - accuracy: 0.7855"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.4268 - accuracy: 0.7855\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 4s - loss: 0.5103 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  3/152 [..............................] - ETA: 3s - loss: 0.4581 - accuracy: 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\r",
      "  6/152 [>.............................] - ETA: 3s - loss: 0.5238 - accuracy: 0.6667"
     ]
    },
    {
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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\r",
      "  9/152 [>.............................] - ETA: 3s - loss: 0.4560 - accuracy: 0.7222"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/152 [==>...........................] - ETA: 3s - loss: 0.3377 - accuracy: 0.8056"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/152 [===>..........................] - ETA: 3s - loss: 0.3592 - accuracy: 0.8333"
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 3s - loss: 0.3779 - accuracy: 0.8125"
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 51/152 [=========>....................] - ETA: 2s - loss: 0.3688 - accuracy: 0.8431"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 57/152 [==========>...................] - ETA: 2s - loss: 0.3793 - accuracy: 0.8421"
     ]
    },
    {
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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\r",
      " 60/152 [==========>...................] - ETA: 2s - loss: 0.3764 - accuracy: 0.8417"
     ]
    },
    {
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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\r",
      " 63/152 [===========>..................] - ETA: 2s - loss: 0.3972 - accuracy: 0.8175"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 76/152 [==============>...............] - ETA: 1s - loss: 0.4195 - accuracy: 0.8026"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "106/152 [===================>..........] - ETA: 1s - loss: 0.4100 - accuracy: 0.7925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/152 [====================>.........] - ETA: 1s - loss: 0.4065 - accuracy: 0.7936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/152 [=====================>........] - ETA: 0s - loss: 0.4051 - accuracy: 0.7946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.4075 - accuracy: 0.7957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.4113 - accuracy: 0.7924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.4103 - accuracy: 0.7934"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/152 [=======================>......] - ETA: 0s - loss: 0.4158 - accuracy: 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\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.4209 - accuracy: 0.7913"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.4179 - accuracy: 0.7885"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.4177 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/152 [=========================>....] - ETA: 0s - loss: 0.4141 - accuracy: 0.7904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.4101 - accuracy: 0.7950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.4086 - accuracy: 0.7923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "145/152 [===========================>..] - ETA: 0s - loss: 0.4052 - accuracy: 0.7966"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/152 [============================>.] - ETA: 0s - loss: 0.4190 - accuracy: 0.7905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.4259 - accuracy: 0.7815"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 4s 24ms/step - loss: 0.4252 - accuracy: 0.7822\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f514c58e940>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_dict_batches = numeric_dict_ds.shuffle(SHUFFLE_BUFFER).batch(BATCH_SIZE)\n",
    "model.fit(numeric_dict_batches, epochs=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xhn0Bt_Xw4nO"
   },
   "source": [
    "## 전체 예제"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zYQ5fDaRxRWQ"
   },
   "source": [
    "Keras에 이기종 DataFrame을 전달하는 경우 각 열에 고유한 사전 처리가 필요할 수 있습니다. DataFrame에서 직접 이 전처리를 수행할 수 있지만 모델이 올바르게 작동하려면 입력이 항상 동일한 방식으로 전처리되어야 합니다. 따라서 가장 좋은 방법은 전처리를 모델에 구축하는 것입니다. [Keras 전처리 레이어](https://www.tensorflow.org/guide/keras/preprocessing_layers)로 많은 일반적인 작업이 처리됩니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BFsDZeu-BQ-h"
   },
   "source": [
    "### 전처리 헤드 빌드하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C6aVQN4Gw-Va"
   },
   "source": [
    "이 데이터세트에서 원시 데이터의 일부 \"정수\" 특성은 실제로 범주형 인덱스입니다. 이러한 인덱스는 실제로 순서가 지정된 숫자 값이 아닙니다(자세한 내용은 <a href=\"https://archive.ics.uci.edu/ml/datasets/heart+Disease\" class=\"external\">데이터세트 설명</a> 참조). 이것들은 순서가 없기 때문에 모델에 직접 입력하는 것은 부적절합니다. 모델은 이를 순서가 지정된 것으로 해석하기 때문입니다. 이러한 입력을 사용하려면 원-핫 벡터 또는 임베딩 벡터로 인코딩이 필요합니다. 문자열 범주형 특성의 경우도 마찬가지입니다.\n",
    "\n",
    "참고: 동일한 전처리가 필요한 특성이 많은 경우 전처리를 적용하기 전에 이들을 함께 연결하는 것이 더 효율적입니다.\n",
    "\n",
    "반면에 이진 특성은 일반적으로 인코딩하거나 정규화할 필요가 없습니다.\n",
    "\n",
    "먼저 각 그룹에 속하는 특성 목록을 작성합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.256500Z",
     "iopub.status.busy": "2022-12-14T20:54:05.255859Z",
     "iopub.status.idle": "2022-12-14T20:54:05.259388Z",
     "shell.execute_reply": "2022-12-14T20:54:05.258727Z"
    },
    "id": "IH2VCyLBPYX8"
   },
   "outputs": [],
   "source": [
    "binary_feature_names = ['sex', 'fbs', 'exang']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.262586Z",
     "iopub.status.busy": "2022-12-14T20:54:05.261993Z",
     "iopub.status.idle": "2022-12-14T20:54:05.265308Z",
     "shell.execute_reply": "2022-12-14T20:54:05.264682Z"
    },
    "id": "Pxh4FPucOpDz"
   },
   "outputs": [],
   "source": [
    "categorical_feature_names = ['cp', 'restecg', 'slope', 'thal', 'ca']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HRcC8WkyamJb"
   },
   "source": [
    "다음으로, 각 입력에 적절한 전처리를 적용하고 결과를 연결하는 전처리 모델을 구축합니다.\n",
    "\n",
    "이 섹션에서는 [Keras Functional API](https://www.tensorflow.org/guide/keras/functional)를 사용하여 전처리를 구현합니다. 데이터 프레임의 각 열에 대해 하나의 `tf.keras.Input`을 생성하는 것으로 시작합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.268750Z",
     "iopub.status.busy": "2022-12-14T20:54:05.268230Z",
     "iopub.status.idle": "2022-12-14T20:54:05.285135Z",
     "shell.execute_reply": "2022-12-14T20:54:05.284422Z"
    },
    "id": "D3OeiteJbWvI"
   },
   "outputs": [],
   "source": [
    "inputs = {}\n",
    "for name, column in df.items():\n",
    "  if type(column[0]) == str:\n",
    "    dtype = tf.string\n",
    "  elif (name in categorical_feature_names or\n",
    "        name in binary_feature_names):\n",
    "    dtype = tf.int64\n",
    "  else:\n",
    "    dtype = tf.float32\n",
    "\n",
    "  inputs[name] = tf.keras.Input(shape=(), name=name, dtype=dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.288363Z",
     "iopub.status.busy": "2022-12-14T20:54:05.287791Z",
     "iopub.status.idle": "2022-12-14T20:54:05.292593Z",
     "shell.execute_reply": "2022-12-14T20:54:05.291985Z"
    },
    "id": "5N3vBMjidpx6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'age': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'age')>,\n",
       " 'sex': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'sex')>,\n",
       " 'cp': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'cp')>,\n",
       " 'trestbps': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'trestbps')>,\n",
       " 'chol': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'chol')>,\n",
       " 'fbs': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'fbs')>,\n",
       " 'restecg': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'restecg')>,\n",
       " 'thalach': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'thalach')>,\n",
       " 'exang': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'exang')>,\n",
       " 'oldpeak': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'oldpeak')>,\n",
       " 'slope': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'slope')>,\n",
       " 'ca': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'ca')>,\n",
       " 'thal': <KerasTensor: shape=(None,) dtype=string (created by layer 'thal')>}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_EEmzxinyhI4"
   },
   "source": [
    "각 입력에 대해 Keras 레이어와 TensorFlow ops를 사용하여 일부 변환을 적용합니다. 각 특성은 스칼라 배치로 시작합니다(`shape=(batch,)`). 각각의 출력은 `tf.float32` 벡터의 배치여야 합니다(`shape=(batch, n)`). 마지막 단계로 모든 벡터를 함께 연결합니다.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ubBDazjNFWiF"
   },
   "source": [
    "#### 이진 입력\n",
    "\n",
    "이진 입력은 전처리가 필요하지 않으므로 벡터 축을 추가하고 이를 `float32`로 캐스팅한 다음 전처리된 입력 목록에 추가하기만 하면 됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.296695Z",
     "iopub.status.busy": "2022-12-14T20:54:05.296439Z",
     "iopub.status.idle": "2022-12-14T20:54:05.321844Z",
     "shell.execute_reply": "2022-12-14T20:54:05.321131Z"
    },
    "id": "tmAIkOIid-Mp"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_5')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_6')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_7')>]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preprocessed = []\n",
    "\n",
    "for name in binary_feature_names:\n",
    "  inp = inputs[name]\n",
    "  inp = inp[:, tf.newaxis]\n",
    "  float_value = tf.cast(inp, tf.float32)\n",
    "  preprocessed.append(float_value)\n",
    "\n",
    "preprocessed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZHQcdtG1GN7E"
   },
   "source": [
    "#### 숫자 입력\n",
    "\n",
    "이전 섹션에서와 같이 이러한 숫자 입력도 사용 전에 `tf.keras.layers.Normalization` 레이어를 통해 실행해야 할 것입니다. 다만 이번에는 dict로 입력된다는 차이가 있습니다. 아래 코드는 DataFrame에서 숫자 특성을 수집하고 적층한 다음 `Normalization.adapt` 메서드에 전달합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.325201Z",
     "iopub.status.busy": "2022-12-14T20:54:05.324712Z",
     "iopub.status.idle": "2022-12-14T20:54:05.521588Z",
     "shell.execute_reply": "2022-12-14T20:54:05.520797Z"
    },
    "id": "UC9LaIBNIK5V"
   },
   "outputs": [],
   "source": [
    "normalizer = tf.keras.layers.Normalization(axis=-1)\n",
    "normalizer.adapt(stack_dict(dict(numeric_features)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S537tideIpeh"
   },
   "source": [
    "아래 코드는 숫자 특성을 적층하고 정규화 계층을 통해 실행합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.525762Z",
     "iopub.status.busy": "2022-12-14T20:54:05.525392Z",
     "iopub.status.idle": "2022-12-14T20:54:05.550959Z",
     "shell.execute_reply": "2022-12-14T20:54:05.550199Z"
    },
    "id": "U8MJiFpPK5uD"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_5')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_6')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_7')>,\n",
       " <KerasTensor: shape=(None, 5) dtype=float32 (created by layer 'normalization_3')>]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_inputs = {}\n",
    "for name in numeric_feature_names:\n",
    "  numeric_inputs[name]=inputs[name]\n",
    "\n",
    "numeric_inputs = stack_dict(numeric_inputs)\n",
    "numeric_normalized = normalizer(numeric_inputs)\n",
    "\n",
    "preprocessed.append(numeric_normalized)\n",
    "\n",
    "preprocessed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G5f-VzASKPF7"
   },
   "source": [
    "#### 범주형 특성"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z3wcFs1oKVao"
   },
   "source": [
    "범주형 특성을 사용하려면 먼저 이를 이진 벡터 또는 임베딩으로 인코딩해야 합니다. 이러한 특성에는 소수의 범주만 포함되어 있으므로 `tf.keras.layers.StringLookup` 및 `tf.keras.layers.IntegerLookup` 레이어 모두에서 지원하는 `output_mode='one_hot'` 옵션을 사용하여 입력을 원-핫 벡터로 직접 변환합니다.\n",
    "\n",
    "다음은 이러한 레이어가 작동하는 방식의 예입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.554732Z",
     "iopub.status.busy": "2022-12-14T20:54:05.554117Z",
     "iopub.status.idle": "2022-12-14T20:54:05.588010Z",
     "shell.execute_reply": "2022-12-14T20:54:05.587401Z"
    },
    "id": "vXleJfBRS9xr"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(5, 4), dtype=float32, numpy=\n",
       "array([[0., 0., 0., 1.],\n",
       "       [0., 1., 0., 0.],\n",
       "       [0., 1., 0., 0.],\n",
       "       [0., 0., 1., 0.],\n",
       "       [1., 0., 0., 0.]], dtype=float32)>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab = ['a','b','c']\n",
    "lookup = tf.keras.layers.StringLookup(vocabulary=vocab, output_mode='one_hot')\n",
    "lookup(['c','a','a','b','zzz'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.591362Z",
     "iopub.status.busy": "2022-12-14T20:54:05.590858Z",
     "iopub.status.idle": "2022-12-14T20:54:05.610501Z",
     "shell.execute_reply": "2022-12-14T20:54:05.609881Z"
    },
    "id": "kRnsFYJiSVmH"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(3, 5), dtype=float32, numpy=\n",
       "array([[1., 0., 0., 0., 0.],\n",
       "       [0., 0., 1., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.]], dtype=float32)>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab = [1,4,7,99]\n",
    "lookup = tf.keras.layers.IntegerLookup(vocabulary=vocab, output_mode='one_hot')\n",
    "\n",
    "lookup([-1,4,1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "est6aCFBZDVs"
   },
   "source": [
    "각 입력에 대한 어휘를 결정하려면 해당 어휘를 원-핫 벡터로 변환하는 레이어를 만듭니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.613743Z",
     "iopub.status.busy": "2022-12-14T20:54:05.613262Z",
     "iopub.status.idle": "2022-12-14T20:54:05.719015Z",
     "shell.execute_reply": "2022-12-14T20:54:05.718268Z"
    },
    "id": "HELhoFlo0H9Q"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name: cp\n",
      "vocab: [0, 1, 2, 3, 4]\n",
      "\n",
      "name: restecg\n",
      "vocab: [0, 1, 2]\n",
      "\n",
      "name: slope\n",
      "vocab: [1, 2, 3]\n",
      "\n",
      "name: thal\n",
      "vocab: ['1', '2', 'fixed', 'normal', 'reversible']\n",
      "\n",
      "name: ca\n",
      "vocab: [0, 1, 2, 3]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for name in categorical_feature_names:\n",
    "  vocab = sorted(set(df[name]))\n",
    "  print(f'name: {name}')\n",
    "  print(f'vocab: {vocab}\\n')\n",
    "\n",
    "  if type(vocab[0]) is str:\n",
    "    lookup = tf.keras.layers.StringLookup(vocabulary=vocab, output_mode='one_hot')\n",
    "  else:\n",
    "    lookup = tf.keras.layers.IntegerLookup(vocabulary=vocab, output_mode='one_hot')\n",
    "\n",
    "  x = inputs[name][:, tf.newaxis]\n",
    "  x = lookup(x)\n",
    "  preprocessed.append(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PzMMkwNBa2pK"
   },
   "source": [
    "#### 전처리 헤드 조립하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GaQ-_pEQbCE8"
   },
   "source": [
    "이 시점에서 `preprocessed`는 모든 전처리 결과의 Python 목록일 뿐이며 각 결과의 형상은 `(batch_size, depth)`입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.723179Z",
     "iopub.status.busy": "2022-12-14T20:54:05.722594Z",
     "iopub.status.idle": "2022-12-14T20:54:05.727294Z",
     "shell.execute_reply": "2022-12-14T20:54:05.726643Z"
    },
    "id": "LlLaq_BVRlnO"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_5')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_6')>,\n",
       " <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'tf.cast_7')>,\n",
       " <KerasTensor: shape=(None, 5) dtype=float32 (created by layer 'normalization_3')>,\n",
       " <KerasTensor: shape=(None, 6) dtype=float32 (created by layer 'integer_lookup_1')>,\n",
       " <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'integer_lookup_2')>,\n",
       " <KerasTensor: shape=(None, 4) dtype=float32 (created by layer 'integer_lookup_3')>,\n",
       " <KerasTensor: shape=(None, 6) dtype=float32 (created by layer 'string_lookup_1')>,\n",
       " <KerasTensor: shape=(None, 5) dtype=float32 (created by layer 'integer_lookup_4')>]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preprocessed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U9lYYHIXbYv-"
   },
   "source": [
    "`depth` 축을 따라 전처리된 모든 특성을 연결하여 각 사전-예제가 단일 벡터로 변환되도록 합니다. 벡터에는 범주형 특성, 숫자 특성 및 범주형 원-핫 특성이 포함됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.730863Z",
     "iopub.status.busy": "2022-12-14T20:54:05.730304Z",
     "iopub.status.idle": "2022-12-14T20:54:05.742683Z",
     "shell.execute_reply": "2022-12-14T20:54:05.742004Z"
    },
    "id": "j2I8vpQh313w"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KerasTensor: shape=(None, 33) dtype=float32 (created by layer 'tf.concat_1')>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preprocesssed_result = tf.concat(preprocessed, axis=-1)\n",
    "preprocesssed_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OBFowyJtb0WB"
   },
   "source": [
    "이제 해당 계산에서 모델을 생성하여 재사용할 수 있도록 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.746248Z",
     "iopub.status.busy": "2022-12-14T20:54:05.745725Z",
     "iopub.status.idle": "2022-12-14T20:54:05.753935Z",
     "shell.execute_reply": "2022-12-14T20:54:05.753275Z"
    },
    "id": "rHQBFHwE37TO"
   },
   "outputs": [],
   "source": [
    "preprocessor = tf.keras.Model(inputs, preprocesssed_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:05.757383Z",
     "iopub.status.busy": "2022-12-14T20:54:05.756875Z",
     "iopub.status.idle": "2022-12-14T20:54:06.174802Z",
     "shell.execute_reply": "2022-12-14T20:54:06.173596Z"
    },
    "id": "ViMARQ-f6zfx"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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79K1NZN1rj77VPRG1jL59+2Lr1q34/fff4ePjgwULFqBv376IjIxERUWF1PGoCbp27Yrk5GS8+uqrCAoKQmhoKL/zICIiIiKiRuFkSSKiBri6uqJr1644efKkRuu7uLggOjq6wfc2btwIBwcHLFq0CImJiSgpKUFOTg6ef/55FBQUIDIyUvVILHVt3LgRffr0wcsvv4ykpCQUFxfjxo0biI6OxltvvYXNmzfXuevDzJkzIZPJcO7cuXrbOnHiBABgwoQJGmVpKawr/akrorZCX9oVIimx/9YejgOI9B/bRO3RtzaRda89+lb3RNSyevXqhcjISJw9exaTJk3C0qVL8fjjj+Pzzz9HZWWl1PFIQ4aGhoiIiEBsbCw+++wzeHl54erVq1LHIiIiIiIiXSeIiFoJACIuLq7Ry//f//2fACA++eSTBt9fvny5MDQ0FJcuXVKVFRUVCQB1Xm5ubg/8jL///e/C2tq6Xvm1a9fEokWLhIODgzAyMhIdO3YUEydOFAcPHlQtk5aWVu+zVqxYodrX+1/PPPOMar3r16+LxYsXC0dHR2FkZCS6dOkiJkyYIJKTk+vlGDdunGjfvr2oqqqq955cLhfdu3cX9+7da3Df2rVrJ4YNG/bAfX+QuLg4oW73w7qSpq4CAgJEQECA2uuRbmJ9Nl1ra1dIM+qON+jB2nr/3RClUlnvs2tfn376aYPrPGocQOrTZLxKbUdznR9sE+vTtTaxucbTrPv6dK3uOf4jan0uXLggFi5cKExMTESvXr1EdHS0qKyslDoWNcEvv/wiHBwcRI8ePcTRo0eljkNERERERLorXiaEEI+aUElEpA9kMhni4uIQGBjYqOX//e9/44UXXsAnn3yCV155pd77xcXFcHFxgY+PD6KiorQdV3K3bt2CnZ0dZsyYgU8//bTOeydPnsTgwYPx1VdfYfr06Q2ub2hoiCFDhiA9PV2tz42Pj0dQUBDU6X5YV9LUlVwuBwAoFArNgpNOYX0SaYe64w16sLbcf2tLY8YBpD5NxqvUdjTX+cE2semau01srvE0677pmrvuOf4jar3+/PNPvPPOO4iOjoatrS2WL1+Ol19+mU9l0FPXr1/Hc889h5SUFGzZsgUvv/yy1JGIiIiIiEj3KPgYbiKiB+jYsSOUSiUSEhKwZcsWqeNolRACCxcuRIcOHbB27do67+Xl5cHf3x9vvPGG3vzozrrSn7oiIiKq1Vb7b23hOICodWGb2DT63Cay7ptGn+ueiKTXs2dPREZGIjs7G35+fli4cCH69euHmJgYVFVVSR2P1GRtbY2kpCSEhoZizpw5CAkJwb1796SORUREREREOoaTJYmozfv73/8OmUyG9u3b13tv8ODByMzMRFJSEm7fvi1BuuZx5coV5OXl4eDBg7C1ta3zXnR0NNavX4/169fXW2/ZsmWQyWSQyWSorq5uqbgqrCv9qSsiIqLGaIv9t7Y8bBxARPqJbaLm9L1NZN1rTt/rnoh0Q69evVSTJqdMmcJJk3qsXbt2iIiIwK5du7Bz506MGzcOBQUFUsciIiIiIiIdwsdwE1Grwcci6Qc+1lB/8LHNrQvrk0g7ON4gav04XqWH4fnRdnE83XbJZDIMGDAAc+fOxbRp0+Dg4CB1JCJqZhcuXMCGDRuwdetW2Nvb44033uDjufVQdnY2pk2bhuLiYigUCri7u0sdiYiIiIiIpMfHcBMRERERERERERERPUiXLl2wbt06ODo6YvDgwVizZg1OnToldSwiaia9evVCdHQ0/vjjD0yYMAGvvvoqnJyceKdJPdO/f3+kp6dj2LBhGD16NDZt2iR1JCIiIiIi0gGcLElERERERERERERE9AALFixAUVERUlJSMGrUKHz66adwdXWFg4MDQkNDceDAAU6gImqFaidN/v777/D29uakST3UoUMHfP3111i3bh2WL1+OF154AWVlZVLHIiIiIiIiCXGyJBERERERERERERHRQ7Rr1w4eHh6IjIxEfn4+Tp8+jVmzZiE5ORne3t7o1q0bgoODoVQqUVFRIXVcItKi3r17c9KkHpPJZAgLC4NSqcTevXvh4eGB8+fPSx2LiIiIiIgkwsmSRERERERERERERERqcHFxQXh4OM6cOYPc3FysXLkSeXl58PPzg5WVFXx9fREbG4vbt29LHZWItKShSZP9+/dHTEwMqqurpY5Hj/D000/j6NGjqKqqwpAhQ5CcnCx1JCIiIiIikgAnSxIRERERERERERERacjR0RGhoaFITU3F+fPn8d577wEA5syZAxsbG3h7eyMyMhKFhYUSJyUibaidNJmTkwMvL686d5rkpEnd1rdvXxw5cgTjx4/H5MmTsWnTJgghpI5FREREREQtSCb4vwAiaiVkMhmGDx8Oe3t7qaPQQ+Tn5yM9PR0BAQFSR6FHSE9Px/Dhw6FQKKSOQlogl8tVdUpEmktISOB4g6iVqx2v8usSakh8fDyCgoL4/5k2KD09HQA4nm6DEhISEBcXh8DAQLXXvXHjBhITE5GYmIjvvvsO5eXlGDFiBHx9feHv749+/fo1Q2Iiamnnzp1DREQEtm7din79+mHZsmWYMWMG2rVrJ3U0eoiYmBgsWLAATz/9NGJjY9GhQwepIxERERERUfNTcLIkEbUacrlc6ghErc6IESOwePFiqWOQFrz77rtIS0uTOgYREZHe4B+MUEPS0tLw7rvvSh2DiFrY4sWLMWLEiCZto6ysDAcPHoRCocCePXtQXFwMZ2dnyOVy+Pr6ws3NTUtpiUgqnDSpf3766ScEBgaic+fO+Oabb/D4449LHYmIiIiIiJoXJ0sSEREREREREREREbWU6upqpKWlQaFQICEhAZcvX4aDgwN8fX0hl8vh7u4OAwMDqWMSkYby8vKwadMmfP755+jfvz/CwsI4aVKH5efn49lnn8XZs2exbds2TJs2TepIRERERETUfDhZkoiIiIiIiIiIiIhICjU1NTh+/DiUSiV27tyJ7OxsdOnSBZMmTYJcLsfEiRNhbGwsdUwi0gAnTeqPiooKLFiwAJ9//jmWLl2KDRs2cNI6EREREVHrxMmSRERERERERERERES6ICsrC4mJiVAqlThy5Ag6deoELy8v+Pj4YNq0abC0tJQ6IhGp6bfffsPatWsRFxcHFxcXhIeHY9q0aZDJZFJHo7+IiYnBa6+9Bi8vL/z73/9GfMct7wAAIABJREFU586dpY5ERERERETaxcmSRERERERERERERES65sKFC9i9ezcSExNx6NAhGBoawsvLC76+vpg6dSq6du0qdUQiUsOZM2ewZs0aJCQkwNXVFWvWrIGvr6/Usegvjhw5ArlcDnNzc+zatQtPPPGE1JGIiIiIiEh7FLyHPBERERERERERERGRjunVqxdCQ0ORnJyMgoICREdHAwAWLlwIOzs7eHh4IDIyEvn5+RInJaLGcHZ2RlxcHE6dOoW+ffvCz88Prq6uUCgUUkej+7i7u+PEiRPo0aMHRowYgfj4eKkjERERERGRFvHOkkREREREREREREREeqKsrAwHDx6EQqHAt99+i9u3b8PZ2RlyuRyBgYFwdnaWOiIRNcKvv/6KtWvXIiEhAcOGDcPy5ct5p0kdUlVVhZUrV2LTpk2YN28ePvroIxgZGUkdi4iIiIiImoaP4SYiIiIiIiIiIiIi0kd3795FamoqlEol4uPjUVhYCEdHR/j4+EAul2PkyJGQyWRSxySih/j555+xbt06JCYmYuTIkXjrrbcwbtw4qWPR/7d9+3bMmzcPQ4cORVxcHGxsbKSOREREREREmuNkSSIiIiIiIiIiIiIifVdTU4MjR44gMTER33zzDX7//Xf06NEDkydPho+PDyZNmsS7ohHpsLS0NGzYsEE1aXL9+vUYPXq01LEIwIkTJ+Dv74/Kykp8/fXXeOqpp6SOREREREREmlEYSJ2AiIiIiIiIiIiIiIiaxsDAAB4eHoiIiEBOTg5Onz6Nl19+GceOHcOUKVNga2uL4OBgKBQKlJaWSh2XiP5ixIgRUCqVSElJgbGxMcaMGQNvb29kZGRIHa3NGzRoEDIyMuDs7IxRo0bh888/lzoSERERERFpiHeWJCIiIiIiIiIiIiJqxc6dO4c9e/ZAoVAgLS0NJiYmGD9+PORyOaZMmYJOnTpJHZGI/iI1NRUrVqzATz/9BC8vL0RERMDNzU3qWG1adXU11q5di7feegtz587Fhx9+CGNjY6ljERERERFR4/Ex3EREREREREREREREbUVRURGSkpKgUCiwf/9+VFdXY/jw4ZDL5ZDL5bCzs5M6IhHd58CBA3jjjTdw7NgxPPPMM1i7di0GDRokdaw2bc+ePQgODsYTTzyB+Ph4tptERERERPqDkyWJiIiIiIiIiIiIiNqimzdv4sCBA1Aqldi9ezfu3LmDwYMHw8fHB9OnT8eAAQOkjkhE/9+BAwcQFhaGEydO4Nlnn8XatWvRv39/qWO1WdnZ2fD390dRURHi4uIwduxYqSMREREREdGjcbIkEREREREREREREVFbd/fuXSQnJyMxMRHffvstrly5AmdnZ/j6+sLHxwcjR46ETCaTOiZRmyaEQGJiIlatWoVff/0Vzz77LNavX49+/fpJHa1NKikpwYsvvog9e/Zg3bp1CAsLkzoSERERERE9HCdLEhERERERERERERHR/1RXVyMtLQ0KhQLffPMN8vPz0atXL/j5+cHX1xdjxoyBoaGh1DGJ2qyamhp8/fXXWLVqFfLy8jB9+nSsXr0affr0kTpamyOEwL/+9S8sX74czz33HGJiYmBubi51LCIiIiIiahgnSxIRERERERERERER0YNlZWVBoVBAoVDgzJkzsLa2xtNPPw25XI4JEybAxMRE6ohEbVLtpMnly5fjwoULeOmll7Bq1SrY29tLHa3NSUpKwowZM9CrVy988803cHBwkDoSERERERHVx8mSRERERERERERERETUOHl5eVAqlVAoFDhy5AjMzMwwbtw4yOVy+Pn5oWPHjlJHJGpzKisrsWPHDqxZswb5+fl48cUXsXr1atjZ2UkdrU35448/4O/vj8uXL2PHjh3w9vaWOhIREREREdXFyZJERERERERERERERKS+ixcvIikpCUqlEt9//z0MDAzg6ekJHx8fBAYGolu3blJHJGpT7t27h23btuGtt97CtWvXMGvWLKxZswa2trZSR2sz7t69i1deeQX//ve/sX79eixduhQymUzqWERERERE9F+cLElERERERERERERERE1z48YNJCYmIjExEUlJSSgrK8OIESPg6+uLadOmwcnJSeqIRG1G7aTJ8PBw3L59G7Nnz8by5cthY2MjdbQ2IyYmBgsWLMDkyZMRGxvLu+4SEREREekGTpYkIiIiIiIiIiIiIiLtKS8vx4EDB6BQKKBUKnHr1i04OztDLpfD19cXbm5uUkckahPu3LmDLVu24O2338a9e/fw+uuv4/XXX+fEvRby008/ITAwEJ06dcKuXbvw+OOPSx2JiIiIiKit42RJIiIiIiIiIiIiIiJqHtXV1UhLS4NCoUBCQgIuX76M3r17Y8qUKZDL5XB3d4eBgYHUMYlatZKSEnzwwQd45513IJPJsHTpUixYsAAWFhZSR2v18vPzERAQgDNnzuDLL7/EtGnTpI5ERERERNSWcbIkERERERERERERERE1v5qaGhw/fhxKpRJxcXE4e/YsHnvsMUyePBlyuRwTJ06EsbGx1DGJWq2SkhJ8/PHH2LhxI4yMjLBkyRKEhobC1NRU6mitWkVFBRYsWIDPP/8cS5cuxYYNGzhJnIiIiIhIGpwsSURERERERERERERELS8rKwuJiYlQKpU4cuQIOnbsCG9vb/j4+GDatGmwtLSUOiJRq3T9+nW8/fbb+OCDD2BtbY0lS5bglVdegYmJidTRWrWYmBi89tprGD9+PLZv347OnTtLHYmIiIiIqK3hZEkiIiIiIiIiIiIiIpLWhQsXsHv3biQmJuLQoUMwNDSEh4cHfHx8MH36dNjY2EgdkajVuXr1Kt599128//77sLW1xfLlyzF79my0a9dO6mit1rFjx+Dv7w9jY2N88803GDhwoNSRiIiIiIjaEk6WJKLWIz4+XuoIRK1Ojx49MGLECKljkBakpaXh4sWLUscgIiLSG4GBgVJHIB2Un5+PI0eOSB2DiFqYu7s77O3tpY7Rply/fh179+6FQqFAcnIyqqqqMHz4cPj6+uLZZ59F3759pY5I1Kr8+eefWL9+PbZu3Yp+/fph2bJlmDlzJh8V3UyKioowffp0pKWlISoqCsHBwVJHIiIiIiJqKzhZkohaD5lMJnUEolYnICAACoVC6hikBXK5HAkJCVLHICIi0hv8uoQaEh8fj6CgIKljEFELi4uL4yR6CZWVleHgwYNQKBTYs2cPiouL4ezsDLlcDl9fX7i5uUkdkajVOHfuHCIiIvD555/j8ccfx5tvvgm5XC51rFapqqoKK1euxKZNmzBv3jx89NFHMDIykjoWEREREVFrx8mSRNR6yGQyfnmtBbU//rF7oNovQjlZsnVgfRKRJji+oraI42F6GJ4fuovjXWouHA/ploqKCqSkpECpVEKhUKCgoACOjo7w8fGBXC7HyJEj+QfVRFqQlZWFNWvWICEhAcOGDcO6deswfvx4qWO1Sl999RXmzp2LIUOGID4+HjY2NlJHIiIiIiJqzRS8fz4REREREREREREREek8ExMTeHl5ITIyEvn5+UhJSYFcLse+ffvg6ekJGxsbBAcHQ6lUorKyUuq4RHrLxcUF8fHxSE9Px2OPPQYvLy94eHjgxx9/lDpaq/P888/j8OHDyM/Px5AhQ/Dzzz9LHYmIiIiIqFXjZEkiIiIiIiIiIiIiItIrBgYG8PDwQEREBLKzs3H69GnMnz8fZ86cwZQpU2BjY4PAwEDExsaitLRU6rhEeumpp56CUqnE4cOHYWxsjDFjxsDb2xvHjh2TOlqrMmjQIGRkZMDZ2RmjR4/GZ599JnUkIiIiIqJWi5MliYiIiIiIiIiIiIhIr7m4uCA8PByZmZk4d+4cVq9ejZs3b2L27Nno2rUrfH19ERMTg6tXr0odlUjvuLu74z//+Q+Sk5NRXFyMoUOHwtfXFydPnpQ6WqthZWWFffv2Yc2aNQgJCUFISAju3bsndSwiIiIiolaHkyWJiIiIiIiIiIiIiKjV6N27N0JDQ5GcnIyCggJERUUBAF577TXY2dnBw8MDkZGRuHTpksRJifSLl5cXjh49iv379+PSpUt48sknERgYiD/++EPqaK2CTCZDWFgYdu/ejbi4OLi7u+PPP/+UOhYRERERUavCyZJERERERERERERERNQqPfbYYwgODoZSqcSNGzewa9cuODo6YtWqVbC3t1fdkfK3336TOiqR3vDy8kJmZiZ27tyJkydPwtnZGcHBwTh37pzU0VoFX19fHD16FOXl5RgyZAj+85//SB2JiIiIiKjV4GRJIiLSmvbt20Mmk9V5bd68WepYGmlN+0LU3OLi4jBo0CCYmZmprpfTp09LHYuozbl58yaioqIwbtw4WFlZwczMDP369cOMGTNa9NFo1dXViIqKgru7Ozp27AgjIyPY2dnh6aefxkcffYTz58+rlt28ebOq3bC3t2+xjC0lMzMTL774Inr37g1TU1N06tQJQ4cOxVtvvYVbt241efu6Pl7RVv3u3LlTtR1TU1MtJiTSLW1lTBUVFVWv7frra/Lkyc2eY9CgQY/Mcf9r3bp1Dba7D3p99tln9T6T/QL7BZKehYUFfH19ERsbi6tXryI5ORleXl6IioqCs7Mz+vTpg9DQUKSmpkIIIXVcIp1mYGAAuVyO3377Ddu3b8eRI0cwYMAAhISEoKCgQOp4es/JyQnp6ekYNWoUJk6ciE2bNkkdiYiIiIioVeBkSSIi0prS0lIcP34cAODn5wchBJYsWSJxKs20pn0hak6HDx/Gc889hwkTJqCoqAh//PFHq5zwRK1TaWkp+vXrBx8fH6mjaMU///lPvPbaa/Dz88OZM2dw/fp1bN26FSdOnICbmxt2797dIjleeOEFvPrqq5g6dSqysrJQUlKClJQUDB48GAsXLsSQIUNUyy5ZsgRCCLi6utbbTlPrR+r6feONNzB8+HB07twZiYmJuHXrFs6dO4fVq1dj165dcHJywuHDh5v0Gbo+XnlY/apj+vTpEEJg/PjxWkpGpHs4pqrL3d29RT5HoVBACKF6hYSEAACSkpLqlAcFBQFouN1t6DV69Oh6n8V+gf0C6R5TU1N4eXmpHsedkpICuVyO7777Dp6enujduzdCQkKgVCpRWVkpdVwinXX/pMkPP/wQiYmJ6NevH5YtW4abN29KHU+vWVpaQqFQYN26dVixYgVmzJiBsrIyqWMREREREek1TpYkIqI2q3379vDw8JA6BpFOe9R1UvsDc2hoKNq3b48+ffrg4sWLeOKJJ1owZevBdkn7HnZMhRCoqalBTU2NWuvpspdffhmhoaGwtbWFubk5PD098dVXX6G6uhpLly5t9s/PyMjAjh07MHv2bCxduhT29vYwNTVFnz59sH79evz9739v9LYeVj8tsX5TrFu3DhEREdiyZQvee+89PPHEEzA1NUXnzp3h4+ODw4cPo2fPnpg8eTLOnj3b4vmIqOW1pjGVNvrIB000zMnJgYmJCebOnaultLqB/QKR7mvXrh08PDwQERGB33//HadPn8ZLL72EY8eOYcqUKejWrRuCg4OhUChw584dqeMS6SQjIyPMmzcPeXl5ePfdd7Ft2zb06tULy5YtQ3FxsdTx9JZMJkNYWBgSExORlJSEkSNH8nHnRERERERNwMmSRERERKSxixcvAgCsra0lTkKkPktLS+Tm5uK7776TOopWfPbZZ4iOjq5X7urqCjMzM+Tm5jb7owSzsrIAAP3792/w/cDAwEZvq6n1I1X9/vHHH1izZg2efPJJ1R3K/src3BzvvfceSkpKsHDhwhbNR0S6qS2Nqfr27QtPT88G3/vwww8xdepU2NraNnuOEydOICAgoFHL7ty5EytXrmz0tg8dOoQ5c+YAYL9ApK9cXFwQHh6OzMxM5ObmYtWqVcjLy0NQUBC6du2qepQ3J4AR1WdiYoJ58+bh999/x5IlSxAVFYW+ffvinXfeQXl5udTx9NakSZNw4sQJGBoaYujQodi/f7/UkYiIiIiI9BInSxIRERGRxqqrq6WOQESPcOfOHZSXl+OJJ56ATCZr1s+ysbEBACQnJzf4/ujRo3Ht2rVmzSC1qKgoVFVVQS6XP3Q5T09P2NnZITk5GXl5eS2Ujoh0VVsaU3l5eeEf//hHvfKSkhJ8+eWXmD9/vgSptGPBggVYtGhRnTL2C0T6z9HREaGhoUhNTcWVK1fwySefAADmzp0La2treHh4IDIyEpcvX5Y4KZFusbS0xJtvvom8vDzMmTMHq1evRr9+/RATE8NH22uoZ8+eSElJga+vL55++mmEh4dL8jQFIiIiIiJ9xsmSREQAioqKsHDhQvTu3RvGxsbo0qUL/P39ceLECdUyHh4ekMlkqtfMmTMB/PeHnvvLb926BQCoqqpCXFwcvL29YWtrCzMzMwwcOBCRkZF1vsDYvXt3nfXPnz+PoKAgdOrUCdbW1vDx8UFubm69zGfPnsXUqVPRsWNHmJub46mnnkJiYmKdPLV3spCauvu4efNm1bL29vbIyMjA+PHjYWlpCXNzc4wdOxaHDx9WLb9u3TrV8vc/Dm7fvn2q8scee6ze9u/cuYPDhw+rljE0NNR4HxtT37du3apzHGQyGdatW6da//7y++9w0pjz86/HODs7G4GBgbC2tlaVtfbJKaRdj7pOas+5b7/9FgBgZmYGmUyG4cOHt0i+69evY/HixejTpw+MjY3RuXNnTJ48GT/88EO9fWhsW1JLm9dcY/uCxrZLjdnvxmarqKjAm2++iQEDBsDc3BxWVlbw9fXFnj17WnzChrp9WmPqqLHncO3r7t27jVpPnQx//YwLFy4gKCgIlpaWsLa2xgsvvICbN2/i/Pnz8PX1haWlJbp164a5c+eipKREa8dXoVAAAFasWKG1bT6Ip6cnbG1t8f3332Py5Mk4dOiQRj/cPKh+at1/LZiYmMDe3h5eXl7Ytm0bysvLH7h+S4y7fvzxRwD/vaPno9Quk5KSonGbpQ5Nx6faOnfPnj2LZ555RnUcH7RP9x9vCwsLeHp6IjU1tUn7RCSV5hpTPaodBNS7PhozLmiO/0fd74svvkDPnj0xatQorWxPV7BfYL9ArUuXLl0QHBwMpVKJwsJC7NixA46Ojli5ciV69OiBIUOGIDw8HNnZ2VJHJdIZVlZW2LhxI86fP4+ZM2ciNDRUNWmyLf3BiLaYmpriiy++wMcff4wNGzZg6tSpvMstEREREZE6BBFRKwFAxMXFqb3e5cuXRa9evYSNjY3Yu3evKCkpEadPnxajR48Wpqam4siRI6plT5w4ISwsLISrq6soLS0VQghx9+5dMWzYMLFjx44621UqlQKA2LBhg7hx44YoKioSH3zwgTAwMBBLliypl8PPz08AEH5+fuLIkSOitLRUJCcnCzMzMzF06NA6y/7++++iU6dOonv37mL//v2qzF5eXqJLly7CxMRE7eNQKy4uTjSlezh+/LhqP/5KnX0UQghXV1dhYWEhRowYoVo+IyND/O1vfxPGxsbi0KFDdZa3sLAQI0eOrLcdNzc3YW1tXa/8Qcs3Zl/+Sp36njhxojAwMBB//PFHve2MGDFCbN++XfVvdc5PIf53jEePHi1++OEHcefOHZGeni7atWsnioqKHrkf9wsICBABAQFqrUO6S9P6fNR1UnvOlZeXNyWeWgoKCoSDg4OwsbERSqVSFBcXi+zsbOHv7y9kMpn49NNP6yyvTlui7WtO3b7gYcdb3f1+VLY5c+aIjh07iv3794uysjJRWFgolixZIgCIH374QcPaUZ+6fZq6daTpOfyw9TQ9T/z9/UVmZqYoLS0VsbGxAoCYPHmy8PPzE8ePHxclJSUiKipKABCvv/66OofxgQoLC4WNjY2YM2eORutrMr5KSUkRPXr0EAAEANG1a1cxY8YM8dVXX4k7d+40uI6rq6vo3r17vfKG6qf2WrC1tRVKpVLcvn1bFBYWirVr1woA4r333nvo+veXN8e4q1u3bgKA+Pnnnx95rGbOnKlqI+4/FuqMf5prvHL/cWrquevq6io6duwoxo4dK1JTU0VJSckD96mh433q1CkxYcIE0bt373rHW919aoymjoepddP0/NDmmKqx7aA614c644JH7YsmampqhJOTk/j444813oY2/v8SEhIiAIikpKQHLlPb7j7oFRoaWmd59gv63y9o+n0TtS1lZWViz549Yt68eaJr164CgHB2dhZhYWEiJSVF1NTUSB2RSGdcuHBBzJs3TxgaGgpnZ2cRHx/Pa0RDP/30k7C1tRVOTk4iKytL6jhERERERPognt/+E1GroemX17NmzRIA6kxQE+K/P0CZmJgINze3OuXx8fGqHwdqamrErFmzxPLly+ttV6lUijFjxtQrnzlzpjAyMhLFxcV1ymt/dFAqlXXKAwICBIA6E93kcrkAIBISEuose/XqVWFubq7zkyUbs49C/PcHFADi+PHjdcpPnTolAAhXV9c65VJPlmxsfX///fcCgJg/f36dZVNTU0X37t3FvXv3VGXqnp+1x/i77757ZOZH4WTJ1qU1TZZ88cUXBYB6k9Tv3r0r7OzshJmZmSgsLFSVq9OWaPuaU7cveNjxVne/H5XNwcFBuLu71yt3cnJq0cmS6vZp6tZRc0yW1PQ82bt3b51yFxcXAUD8+OOPdcodHBxE//79H5i5sa5duyYGDRokgoKCRFVVlUbb0HR8dffuXfHll18KPz8/YWlpqZpAYm1tXe8cFkK9yZK110JDuSZNmqTWZMnmGHfVToo5evRoQ4emjtpJMRs3blSVqTv+aa7xihDaO3dr9yktLe2R+/Sg433p0iVhYmLS4KQYdfapMThZkh5GFyZLNrYdVOf6UGdc0ByTJffu3SssLS1FSUmJxtto6cmSDbW7r7766gMnS7Jf+B996xc4WZLUVVVVJVJSUsTChQtF9+7dBQDRu3dvsXDhQpGcnCwqKyuljkikE3777Tchl8uFTCYTw4YNEwcPHpQ6kl7Kz88Xw4cPF5aWlvX6SyIiIiIiqieej+EmojZv9+7dMDAwgI+PT51yW1tbuLi44NixY8jPz1eVy+VyrFixAt988w08PDxw/fp1rF27tt52fXx86jwWtZarqysqKyuRlZXVYJ6hQ4fW+XePHj0AAJcvX1aV7du3DwAwceLEOst26dIFAwYMeNju6oTG7GMtCwsLDBo0qE7ZwIEDYWdnh5MnT6KgoKD5gqpBnfqeMGECBg4ciG3btuH69euq8rfffhuvvfYajIyMVGXqnp+1nnrqKW3sFpFO2rVrFwDgmWeeqVNuYmKC8ePHo7y8HN9//32d9xrblmj7mtO0L2iIJvv9sGyTJk3CkSNHMG/ePKSnp6sefZWdnY0xY8Y0OldTqdunaVpH2qRphiFDhtT5t52dXYPl3bt3b7BPVMedO3cwceJEODs7Y/v27WjXrl2TtqcuExMTBAcHY/fu3bhx4wYOHjyI6dOn4/r165g5cyaOHz+u8bZrr4XJkyfXey8pKQmLFi1q9LaaY9xVW6/39/EPUrtM7Tq1mmv8o2mbpI1z19TUFMOGDatT1tA+Peh429nZwcnJSWv7RKTPGtsOqnN9SD0u+OCDDxAcHIz27ds3+2e1NPYL7Beo7WnXrh08PDwQGRmJ/Px8nD59GrNmzUJycjK8vb3RrVs31aO8KyoqpI5LJJkBAwYgPj4eJ0+eRM+ePTF+/Hh4e3sjIyND6mh6pXv37jh06BCmT58OuVyOZcuWoaamRupYREREREQ6i5MliahNq6ioQHFxMWpqatCxY0fIZLI6r19++QUA8Pvvv9dZb+3atRg2bBiOHDkCuVwOA4P6zWlxcTHefPNNDBw4EJ07d1Zt85///CcAoKysrMFMHTt2rPNvY2NjAFB9wVFRUYGSkhKYmpo2+ENS586d1TwKLe9R+3i/Tp06NbiNrl27AgCuXr2q5XSaUbe+Fy1ahLKyMnz88ccAgJycHPznP//BvHnzVMtoen4C//0xjag1qr0uTE1NYWlpWe99GxsbAEBhYWGd8sa0Jc1xzWnaF2hrvx+WbcuWLYiNjUVeXh7Gjx+PDh06YNKkSaoJGC1B3T6tKXWkzcyaZujQoUOdfxsYGKBdu3YwNzevU96uXbsm/bBRVVUFuVyO7t2748svv2zxiZJ/ZWhoiHHjxmHHjh0ICwtDdXU1EhISNNrWo64FdTXHuGv06NEAgBMnTjzy80+ePAkA9SYiNdf4R9M2SRvnrrW1NWQyWb3yv7bDDzvetctqY5+I9JU67aA614eU44KcnBzs378f8+fPb/bPam4fffQR3n///Tpl7BfYLxC5uLggPDwcZ86cQW5uLlauXIm8vDz4+fnBysoKvr6+iI2Nxe3bt6WOSiSJgQMHIj4+HqmpqaisrMRTTz0Fb29vVb9Ij2ZiYoKYmBhs27YNH3zwAXx8fHDz5k2pYxERERER6SROliSiNs3ExASdOnWCoaEhKisrIYRo8DV27Ng66x06dAjFxcUYOHAg5s+f3+AXN76+vli7di3mzp2LnJwc1NTUQAiB9957DwAghNA4s6WlJe7evYvS0tJ67+vK5EFtuX79eoPHqnY/7/9xxMDAAPfu3au37K1btxrcdkM/zGhK3fqeMWMGbGxs8NFHH6GiogLvvPMOZs2aVWfShabnJ5E2afM60QYTExN07NgRd+/eRUlJSb33r1y5AuC/d/i7X2Pakua45tRtGx50vDXd74eRyWR44YUXcODAAdy6dQu7d++GEAL+/v549913G72dplC3T9OkjjQ9hx9WF7reNoeEhKCiogLx8fEwNDRUlfft2xfp6enN+tmHDx9WTd5tSO1x0fRHm0ddC9qmybgrJCQEhoaGUCgUD912amoqLl++DF9fX/Ts2bPOe+qMf9TRXOPTxiguLm6w/K/t8MOO940bN+qVSbkMTvKmAAAgAElEQVRPROrQ1phKnXZQnetDnXGBtseHH3zwAUaNGgVnZ2etbldXsF9oGPsFaqscHR0RGhqK1NRUnD9/XnVuzpkzBzY2NvD29kZkZGSDfwhH1NqNHDkShw4dQnJyMq5fv44nn3wSgYGByM3NlTqa3ggODkZqairOnDmDoUOH4tSpU1JHIiIiIiLSOZwsSURtnr+/P6qqqnD48OF6723atAk9e/ZEVVWVquzcuXOYPXs2vv76a+zZswdmZmbw8/NDUVGRapnq6mocPnwYtra2WLhwIbp06aL6Qam8vLzJmWsft1b7OKpahYWFyMnJafL2dcndu3frPXrl119/xeXLl+Hq6opu3bqpyrt164ZLly7VWbawsBB//vlng9s2NzevM7myf//+iImJUSufoaEhsrKy1K5vExMTzJ8/H1evXsU777yD7du3IzQ0tN5y6p6fRNqmjetE26ZNmwYA2Lt3b53yiooKHDx4EGZmZvUe09fYtkSb15wmfcHDjrcm+/0wnTp1wtmzZwEARkZG8Pb2xu7duyGTyep9RnNSt09Tt440PYcftp4ut83h4eHIysrCt99+CxMTkxb/fCEErl69+sBJmZmZmQCAwYMHa/wZtdfCd999V++9wYMH4/XXX9d42w1R9xx1cnLC6tWr8csvvyA6OrrBbZaVlWHRokWwtraudwcyQL3xT2NoOl7RptLS0np/YNTQPj3oeF+7dg3Z2dl1ypp7zE2kTdocUzWmHVT3+lBnXKDNfbl9+zZiY2Px6quvarS+PmC/0DD2C0RAz549MW/ePCiVShQWFiI6OhqdO3fGihUr0L17d3h4eGDTpk3Neud8Il3k5eWFY8eOYefOnThx4gQef/xxhISEoKCgQOpoeuHJJ59EZmYmevfujWHDhuHLL7+UOhIRERERkU7hZEkiavM2btyIPn364OWXX0ZSUhKKi4tx48YNREdH46233sLmzZtVd2UqLS3F1KlT8f7778PZ2Rm9e/dGQkICLl++jICAAFRWVgL476OmxowZg8LCQrz99tu4du0aysvL8cMPPyAqKqrJmTds2AArKyssWrQIycnJKC0txenTp/HSSy+pdVcxfdCxY0csX74caWlpuHPnDjIzMzFz5kwYGxsjMjKyzrITJkzA5cuX8dFHH6G0tBS5ubkIDQ194F02nnzySeTk5ODixYtIS0tDXl4ePD091c6oaX3Pnz8fZmZmWLlyJby8vNC3b996y6hzfhI1B02uk/Pnz6Ndu3Z1HkmsTRs3boSDgwMWLVqExMRElJSUICcnB88//zwKCgoQGRlZ7852jW1LtHnNadI2POx4a7Lfj/LKK6/g1KlTqKiowNWrV/Gvf/0LQgiMGzdOre00xoPOC3X7NHXrSNO2/lF1oYtt87Zt27BmzRr8/PPPsLS0rPeI8Ja8G0dgYCC++uorXL58GRUVFTh//jw2b96Mt956C25ubggODtZ427XXwuuvv469e/eipKQE+fn5mD9/PgoKCrQ+WVKTcdfKlSvxxhtv4NVXX8XixYuRlZWFiooK3Lp1C4mJifDw8EBhYSG+//57ODo61ltfnfFPYzX3+PRRLCwssGDBAvz8888P3aeGjveZM2cwc+bMeo9glXqfiNShzTFVY9pBTa6Pxo4LtPX/KADYunUr2rdvr5oA2lqxX6iP/QJRXVZWVggODkZ8fDyuXr2K3bt3w9HRERs3boSTk5PqUd7Hjh2TOipRi5DJZJDL5cjKysJnn32G/fv3o2/fvli2bBkfL90Ijz32GPbt24fQ0FC8+OKLCAkJUf12QURERETU5gkiolYCgIiLi9No3evXr4vFixcLR0dHYWRkJLp06SImTJggkpOTVcu8+uqrAoDq9euvv4qioqI6ZQDE2rVrhRBCFBUViZCQENGjRw9hZGQkbGxsxIsvviiWLVumWtbNzU2kpaXV28aKFStU+3T/65lnnlHlyc7OFlOnThUdOnQQ5ubmwt3dXfz4449izJgxwtzcXOPjGBcXJzTtHiwsLOplfvvttzXeR1dXV9G9e3dx5swZMXHiRGFpaSnMzMzE6NGjRWpqar3Pv3XrlpgzZ47o1q2bMDMzEx4eHiIjI0O4ubmpth8WFqZa/uzZs8LT01NYWFiIHj16iC1btjx0Xx70+u233xpd3381d+5cAUD8+OOPDzyujTk/GzrGTe3mAwICREBAQJO2QbpD0/p80HWya9euBs+5tLQ0ce7cOWFgYCBkMpk4deqUtndFCCHEtWvXxKJFi4SDg4MwMjISHTt2FBMnThQHDx6st6y6bYk2rzl124aHtUuN3e/GZjtx4oQICQkRjz/+uDA3NxdWVlZi+PDh4tNPPxU1NTWNqwg1POy8ULdPa0wd1VLnHJ4xY8Yj11Mnw4P6v4yMjHrlGzduFCkpKfXKV69e3ehj/Mwzzzyyz0pLS2v09oRQf3xVXV0tUlNTxZIlS8SwYcOEnZ2dMDQ0FJaWlmLIkCFiw4YN4s6dO6rl33777QaP0aPq56/XQrdu3cT06dNFTk6OEOLB9dvS466MjAwxa9Ys0atXL2FsbKw6DuvWrRO3bt1qcB112qzmGq9o69y9v367d+8ujh49KsaOHSvat2//0Hb4/uNtZmYmhg4dKhITE8X48eNV25s9e7YQQv12tjGaMh6m1k/T80PbY6pHtYNCqHd9qDMueFQf2Vg1NTWib9++4s0339Ro/b9qyv9fvvjiiwbroaSkpM5yDbW7NjY2jf4c9gv62S+oOx4i0qaqqiqRkpIiFi5cKOzs7AQA4eDgIBYuXChSUlJEdXW11BGJWkRFRYWIjo4WNjY2wtLSUoSFhYni4mKpY+mFr776SlhYWAhPT09RUFAgdRwiIiIiIqnFy4QQAkRErYBMJkNcXBwCAwOljiKpAQMGoLy8HBcuXNBo/fj4eAQFBUEXuodBgwbh2rVryM/PlzpKs/niiy+wZcsW1WNJdYlcLgcAKBQKiZOQNrTl+mwLbUlr1dQ+jZqO46uHa45zlG2W9HRpPEy6h+eH7mqt4132C9LjeIh0RU1NDY4fPw6lUomdO3ciOzsbXbp0waRJkyCXyzFx4kQYGxtLHZOoWZWWlmLLli3YuHEjjIyMsGTJEoSGhsLU1FTqaDrt5MmT8Pf3R0VFBRISEjB8+HCpIxERERERSUXBx3ATEemhwsJCWFlZ1Xt0xvnz55Gbm9ssj0+l5hEVFYXFixdLHYOISDLs00jX8RwlIiIiIl1gYGAANzc3hIeH4+zZszh9+jT+8Y9/IC8vD35+frC1tUVgYCBiY2NRUlIidVyiZtG+fXuEhYUhNzcXs2fPxpo1a+Dk5ISYmBhUVVVJHU9nubq6IiMjA0888QTGjBmDTz/9VOpIRERERESS4WRJIiI9dfPmTYSEhODixYsoKyvD0aNHERQUhA4dOmDVqlVSx6MH+OyzzzBt2jSUlpYiKioKN2/e5N0piKjNY59Guo7nKBERERHpGhcXF4SFhSE1NRXnzp3D6tWrcfPmTcyePRtdu3aFr68vYmJicPXqVamjEmmdtbU1IiIikJOTg2nTpuG1117DwIEDoVAoeAfwB7CyskJSUhLWrFmDV155BcHBwSgvL5c6FhERERFRi+NkSSIiPWRra4sDBw7g1q1bGDVqFDp37owpU6agX79+OHr0KBwdHaWO2CSbN2+GTCbDyZMncenSJchkMqxcuVLqWFqze/dudO7cGZ988gl27twJQ0NDqSMRNTuZTKaVV3h4eKM/s7W3JS2hJeqttfdp2qDta4PU01LnKNssItJ37K+0i/0CEamjV69eCA0NRXJyMgoKChAdHQ0AWLhwIezs7ODh4YHIyEjk5+dLnJRIu+zt7REZGYns7GyMGjUKzz33HFxdXaFQKKSOppNkMhnCwsLw7bffQqlUwtPTExcuXJA6FhERERFRi5IJ/okVEbUSMpkMcXFxvEtfE8XHxyMoKIh/gUuQy+UAwC8XWwnWJxFpguMraos4HqaH4fmhuzjepebC8RDps7KyMhw8eBAKhQLffvstbt++DWdnZ8jlcgQGBsLZ2VnqiERalZWVhTVr1iAhIQEjRozAhg0bMHr0aKlj6aScnBz4+/vj6tWr2LlzJ8aNGyd1JCIiIiKilqDgnSWJiIiIiIiIiIiIiIhaGXNzc/j6+iI2NhZXrlxBcnIyvLy8EB0dDRcXF/Tp0wehoaFITU3lHwJQq+Di4oL4+HikpqbCyMgIY8aMga+vL06dOiV1NJ3j5OSEtLQ0jB49GhMnTsSmTZukjkRERERE1CI4WZKIiIiIiIiIiIiIiKgVMzU1hZeXFyIjI3Hp0iWkpKRALpcjKSkJnp6e6NWrF0JCQqBUKlFZWSl1XKImcXd3x6FDh7Bv3z5cvnwZgwcPxsyZM5GXlyd1NJ1iaWmJ+Ph4rFu3DitWrMDzzz+PsrIyqWMRERERETUrTpYkIiIiIiIiIiIiIiJqIwwMDODh4YGIiAjk5OTg9OnTePnll3Hs2DFMmTIFtra2CA4OhkKhQGlpqdRxiTQ2ceJEZGZmYufOncjIyMCAAQMQEhKCgoICqaPpDJlMhrCwMCQnJ+PgwYNwd3fnpFIiIiIiatU4WZKIiIiIiIiIiIiIiKiNcnFxQXh4ODIzM5GXl4c333wTeXl5mD59Orp27ap6lPetW7ekjkqkNplMBrlcjqysLHz00UfYu3cv+vXrh2XLlvGcvs/YsWORmZkJIyMjDB06FN9//73UkYiIiIiImoVMCCGkDkFEpA0ymQzDhw+Hvb291FH0Wn5+PtLT0xEQECB1FJJYeno6hg8fDoVCIXUU0gK5XK6qUyKixkpISOD4itqc2vEwvy6hhsTHxyMoKIj/X9JB6enpAMDxLmldQkIC4uLiEBgYKHUUohZXVFSEpKQkKBQK7N+/H9XV1Rg+fDjkcjnkcjns7Oykjkiktnv37mHbtm1YuXIlqqursXTpUixcuBBmZmZSR9MJd+/exfz587Ft2zYsXboUGzZsgIEB771DRERERK2GgqNbIiKqw97eXis//CUkJCA/P18LiYiIiPRbenq6agKHvgkICOBESSIi0gvDhw9v8kTJ/Px8JCQkaCkREZH+69KlC4KDg6FUKlFYWIgdO3bA0dERq1atQo8ePTBkyBCEh4fj7NmzUkclajRjY2PMmzcPubm5WLp0KdavXw8nJyfExMSgqqpK6niSMzU1xdatWxEVFYV3330XU6dORXFxsdSxiIiIiIi0hneWJKJWQyaT8S/9dQjrQ//J5XIA4J0lWwnWJ5F0eP0R6ZfaOwfy6xJqCM+P1o31Sw3h9xtE9d29exfJyclITEzEt99+iytXrsDZ2Rm+vr7w8fHByJEjIZPJpI5J1ChFRUV455138P7776N3795Yu3YtAgICeA4DSE1NhVwuR4cOHfDNN9/AxcVF6khERERERE3FO0sSERERERERERERERFR45iamsLX1xfR0dG4dOkSUlJS4OXlhe3bt8PT0xMODg4IDQ3FgQMHeKc+0nldunRBREQEsrOzMXr0aDz33HMYNmwYDhw4IHU0yXl4eCAzMxNWVlYYMWIEvv76a6kjERERERE1GSdLEhERERERERERERERkdratWsHDw8PREZG4uLFizh9+jRefPFFHDhwAN7e3rC1tVU9yruiokLquEQP1KtXL0RHR+PkyZPo3bs3vL294e3tjczMTKmjSap79+44dOgQXnrpJcjlcixbtgzV1dVSxyIiIiIi0hgnSxIREREREREREREREVGTubi4IDw8HFlZWcjNzcWqVauQl5cHPz8/WFlZwdfXF7GxsSguLpY6KlGDXFxcEB8fj8OHD+PevXsYOnQovL298euvv0odTTImJiaIjIzEl19+iQ8++AA+Pj64ceOG1LGIiIiIiDTCyZJERERERERERERERESkVY6OjggNDUVqaiouXLiA9957DwAwZ84c2NjYwNvbG5GRkSgoKJA4KVF97u7u+PHHH5GcnIyioiIMGjQIgYGBOHfunNTRJPPCCy8gNTUVZ8+exeDBg9v8XTeJiIiISD9xsiQRERERERERERERERE1mx49emDevHlQKpUoLCxETEwMOnfujJUrV8Le3h4eHh7YtGkTcnJypI5KVIeXlxd++eUX7Ny5E8eOHcOAAQMQEhKCq1evSh1NEk8++SQyMjLQr18/eHp6Ytu2bVJHIiIiIiJSCydLEhE1QmlpKfr16wcfHx+poxARkY5g30BERERS4TiEiIj0mZWVFYKDgxEfH4+rV69i9+7dcHR0REREBPr37696lPexY8ekjkoEADAwMIBcLsdvv/2GDz/8EHv27EGfPn2wbNky3L59W+p4Le6xxx7Dvn37EBoaipdeegkhISGorKyUOhYRERERUaNwsiQRUSMIIVBTU4OamhqpozxS+/bt4eHhIXUMvSf1cZT684no0dg3ELVuUl83Un8+Eek2jkOoKaSuE6k/n4h0i5mZGXx9fREbG4tr164hJSUFXl5e+PTTTzFkyBA4ODioHuWtD/0etW7GxsaYN28e/vjjD6xcuRJRUVHo06cPNm3ahIqKCqnjtShDQ0NERERgx44d2L59O8aPH4/CwkKpYxERERERPRInSxIRNYKlpSVyc3Px3XffSR2FiNq48vJy3LhxQ+oYBPYNRERE+qympkavf8zlOISIiFqjdu3awcPDA5GRkbh48SIyMzMxa9Ys7N+/H56enrCxsUFwcDCUSiXu3bsndVxqwywsLBAWFobc3FzMnj0b4eHhcHJyQkxMDKqrq6WO16KmT5+OI0eO4PLlyxgyZAjS09OljkRERERE9FCcLElERESkRy5dugRbW1v4+Phg586dKCsrkzoSERERkd6pqKiAvb09xo4diy+++AK3bt2SOhIRERHdx8DAAG5ubggPD8dvv/2G06dPY8mSJcjLy4Ofnx9sbGwQGBiI2NhYlJSUSB2X2ihra2tERETg7NmzGDt2LObPnw83N7c29wctf/vb3/DLL79gyJAhGDNmDCIjI6WORERERET0QJwsSUT0CLt374ZMJlO97t6922D5+fPnERQUhE6dOsHa2ho+Pj7Izc1VbWfz5s2qZe3t7ZGRkYHx48fD0tIS5ubmGDt2LA4fPqxaft26darl73881b59+1Tljz32WL3t37lzB4cPH1YtY2ho2AJHSRrXr1/H4sWL0adPHxgbG6Nz586YPHkyfvjhB9Uy2j6OrEfSBZWVlUhKSsLzzz8PKysrPPfcc0hMTERlZaXU0doM9g1EuoFjASJqiurqavz444+YM2cOunTpgilTpkChUKC8vFzqaA/FcUjbwD6OiKguFxcXhIWFITU1FefOnUN4eDhu3ryJ2bNno2vXrvD29kZkZCSuXLkidVRqg3r16oVt27bh119/hZOTE3x8fODu7o6UlBSpo7WYDh06YNeuXVizZg0WL16M4OBgnR9XExEREVEbJYiIWgkAIi4urtm27+fnJwCI8vLyBsv9/PzEkSNHRGlpqUhOThZmZmZi6NCh9bbj6uoqLCwsxIgRI1TLZ2RkiL/97W/C2NhYHDp0qM7yFhYWYuTIkfW24+bmJqytreuVP2j5WmPHjhVWVlYiLS2tsbuukeauj4KCAuHg4CBsbGyEUqkUxcXFIjs7W/j7+wvZ/2PvzsOaOvP2gd8JCZsg4g51A1zBHVxQGG0NaivRigSstkytHe28LthxRnAr2NEK1BnFtiqofVvcCtFiDWor6HQERSu0WoEKCtq6gIK4gKIInN8f/cErBRU04ZDk/lxXLjU5Oec+eZLnPJ48OV+JRNi8eXOt5bX9OhpDO/r6+gq+vr46Wz89n5ycHAFArZtcLhcACFZWVsKbb74p7Nu3T3j06FGt57E9dYPHBmoIfv50g2MBfm51JTY2VuDpEsN3//79OmMqExMTQSqVCqampsKUKVOEffv2CeXl5bWe15zeHxyHaF9zaV8e45rPe0IQdH9+g4heTFFRkfDll18K3t7egpmZmWBiYiKMHDlSCAsLE86fPy92PDJSJ0+eFEaPHi0AEBQKhfDzzz+LHalJJSQkCK1atRIGDx4sXLp0Sew4RERERESPi+OVJYmItOTdd9+Fu7s7WrRoAYVCgQkTJuDUqVMoKiqqs+y9e/ewYcOGmuXd3Nywfft2lJeXIzAwUKc5q6qqIAgCBEHQ6XZ0bfHixbh48SLWrVsHb29vtGzZEj179sTOnTthZ2eH+fPn6/yX5GxHai6qryhZWlqKuLg4TJw4Efb29ggMDERKSgrfJyLisYFIdzgW4OeWSNsqKytRVVWF8vJyfPPNN5g4cSLatGmDgIAAJCUl6d3njeMQ/cVjHN8TRNRw1cdqjUaD4uJixMfHw9HREatXr0aPHj3g4uKC0NBQpKenix2VjMjQoUPxn//8B4mJiSgqKsLAgQPh5+eHS5cuiR2tSUyYMAE//PADysvL4ebmhsOHD4sdiYiIiIioBmucEBFpyZAhQ2r9u3PnzgCAa9eu1So7BQAtWrTAwIEDa93Xr18/2Nvb48yZM8jPz4ednZ1Ocn7//fc6WW9Ti4+PB/D7iZfHmZmZYcyYMdi2bRu+++47BAQE6CyDMbTjzZs3oVarm2Rb1DAFBQVPfby8vBwAUFhYiA0bNmD9+vVwcHCAhYVFTb9ETYfHBiLd4Vjge52sl/4Px0CGrXrM9CQVFRUAgJKSEnz11VfYtm0bOnTogGHDhjVFPK3gOER/8Rj3vU7WS0SGz9LSEkqlEkqlEg8fPkRycjI0Gg2io6OxYsUKODo6wtvbGyqVCiNHjoREIhE7Mhk4hUKB9PR07NmzB8HBwXBxccG8efMQHByMVq1aiR1Pp3r06IHU1FTMmDED48ePx8qVKxEUFCR2LCIiIiIiTpYkItIWGxubWv82NTUF8PsVEf7oSSdC2rdvj2vXruHGjRs6+9LBEDx8+BB37tyBubk5rK2t6zzeoUMHAM+eVPaijKEdz58/Dz8/P7Fj0HOq/pL/4sWLAICrV68iKSkJCoVCzFhGhccGIt3gWICaAsdAVK36Kt7Xr1/Hvn37AABxcXHN/j3CcYh+4jGOiEg7zMzMoFAooFAosHbtWhw/fhwJCQmIj4/H+vXr0a5dO4wfPx4qlQrjx4+HXC4XOzIZKKlUCpVKhUmTJuGLL77A8uXLsXnzZixatAjz58+HhYWF2BF1xsrKCnFxcYiIiMDSpUtx+vRpbNmyBS1atBA7GhEREREZMZbhJiISwc2bN+stJ3Xjxg0Av3/5UE0qldZ71ZPbt2/Xu25j+EW0mZkZbGxs8ODBA5SUlNR5vLocWceOHWvu08XraAztOHz48JryZ7w1j1tOTk6D2q76JH91mT6FQgEvLy9OlGzGjKFPIdIWjgWoKYh9zOdNt7f79+836H1QPcGwXbt2mD9/PlasWAHA8CbTsj9rPniMIyLSPqlUCg8PD4SFhSE7OxsZGRn4n//5H2RlZWHixIno0KED/Pz8EBMTg9LSUrHjkoEyNTXFrFmzkJubi0WLFmHVqlXo2bMnoqOjUVlZKXY8nZFIJAgKCkJSUhKOHDmCESNGIDc3V+xYRERERGTEOFmSiEgEDx48wKlTp2rdd/bsWVy7dg0DBgyodXUGOzs7XL16tdayBQUF+O233+pdt6WlZa0vKXr16oXo6Ggtpm8eJk+eDADYv39/rfsfPnyIw4cPw8LCAuPGjau5XxevI9uRmpvqL/NtbGwwY8YMJCcn4+rVq4iMjDT40j6GgH0KUeNwLEBEuiKXyyGRSNCiRQv4+flh3759uHbtGiIjI9G7d2+x4+kE+7Pmhcc4IiLdcnFxQWhoKNLS0nDx4kWEhITg1q1bmDlzJtq3bw+lUono6OiaCeJE2mRlZYWgoCDk5ubCx8cHc+bMQb9+/aBWq8WOplOjR49GWloazMzMMHjwYHzzzTdiRyIiIiIiI8XJkkREIrCxscGSJUuQmpqKe/fuIS0tDW+++SZMTU0RGRlZa9mxY8fi2rVr+PTTT1FaWorc3FwEBgbWuorD4wYPHoycnBxcvnwZqampyMvLg6enZ83jr7zyCtq0aYMTJ07odB91bfXq1XBwcMCCBQuQkJCAkpIS5OTkYNq0acjPz0dkZGRNeTJA+68jwHak5qG+L/OLiooQFRUFDw8PXrVFj7BPIWocjgX4uSXSJhMTE0ilUsjlcnh5eSE2NhbFxcXYtm0blEolZDKZ2BF1iv1Z88JjHN8TRNR0unXrhsDAQCQmJiI/Px+bNm0CAMybNw/29vbw8PBAZGRknUnhRC+qXbt2iIyMRGZmJvr27Qt/f3+4u7vj6NGjYkfTmc6dO+Po0aPw9fXF5MmTERwcjKqqKrFjEREREZGxEYiIDAQAITY2VuvrjY+PFwDUuk2fPl1ITU2tc//SpUtrsjx+mzBhQs36BgwYILz00ktCVlaWMG7cOMHa2lqwsLAQRo0aJaSkpNTZ/u3bt4V3331XsLOzEywsLAQPDw/h1KlTgqura836g4KCapY/d+6c4OnpKbRo0ULo3Lmz8Nlnn9Van6enp2BrayscP35c66/V43TVHo8rKioSFixYIDg4OAhyuVywsbERxo0bJxw+fLjOstp+HY2hHX19fQVfX1+drZ+eT05OTs17xtTUVPD19RX27t0rPHjw4KnPY3tqF48N1Bj8/OkOxwL83OpCbGyswNMlhu/+/fs1nz2ZTCa8+uqrwo4dO4TS0tKnPq85vD84DtGd5tC+1XiMax7vCUFomvMbRNT8lJaWCvv27RPeeustwdraWgAgODs7CyEhIUJWVpbY8cgA/fDDD8Irr7wiABAUCoVw5swZsSPpVFRUlGBqaip4e3sLt27dEjsOERERERmPOIkgCMKLTrgkImoOJBIJYmNj4efnJ3aUpxo4cCCKiopw5coVsaPolL60x/Myhpb1GL0AACAASURBVHZUqVQAYPAlYPRNXl4e5s2bhzfeeAOTJk2CtbV1g57H9mzejKFPMWb8/Bkmfm4NV1xcHPz9/cHTJYbtwYMHGD9+PKZNmwZfX1+0bt26Qc8zxPcH+7P/Y4jt+zz4nqjN0M9vENGzPXjwACkpKdBoNIiNjcX169fh6OgIb29vqFQqjBw5kpU9SGuSkpKwaNEinDlzBlOmTEFERAS6desmdiydOHbsGFQqFaysrBAfHw8XFxexIxERERGR4VOzDDcRERGRHnF0dMT+/fvx5ptvNniiJBERERHVZm5uju+//x6zZs1q8ERJIiIiMk7m5uZQKBQ15biTk5OhUqlw4MABeHp6olu3bpg9ezY0Gg0ePXokdlzScwqFAunp6fjqq6/w448/olevXpg9ezYKCwvFjqZ1I0eORFpaGtq2bYvhw4dj9+7dYkciIiIiIiPAyZJEREREREREREREREREz2BiYgIPDw+EhYXh/PnzyMjIwIwZM5Ceno6JEyfCzs4OAQEBUKvVuHfvnthxSU9JJBKoVCr88ssv+OSTT/DNN9+gV69eCA8PR1lZmdjxtMre3h5Hjx7FnDlz4Ofnh+DgYFRWVoodi4iIiIgMGCdLEhE1kTVr1kAikeDMmTO4evUqJBIJli1bJnYsaiS2IxFpE/sUIv3Dzy0RGQr2Z/RHfE8QETWei4sLQkNDkZaWhtzcXCxfvhx5eXnw9/dH+/btoVQqERMTgzt37ogdlfSQXC7HrFmzcOHCBQQFBeGjjz5Cjx49EB0djYqKCrHjaY1MJkNYWBhiYmKwfv16KBQK3LhxQ+xYRERERGSgJIIgCGKHICLSBolEgtjYWPj5+YkdhcD2MAQqlQoAoFarRU5C2sD2JBIPP39E+iUuLg7+/v7g6RKqD98fho3tS/Xh+Q0ieh6FhYU4ePAg1Go1Dh06hMrKSgwfPhwqlQoqlQr29vZiRyQ9VFRUhDVr1mDdunVwcHDAhx9+CF9fX0gkErGjac1PP/0EHx8fVFZWYs+ePRgyZIjYkYiIiIjIsKh5ZUkiIiIiIiIiIiIiIiIiLWnXrh0CAgKg0WhQUFCAXbt2wdHREcuWLUPnzp3h5uaG0NBQZGdnix2V9Ejbtm0RFhaGs2fPol+/fvD394eHhwdSUlLEjqY1gwYNwqlTp9CrVy/86U9/wv/+7/+KHYmIiIiIDAwnSxIRERERERERERERERHpgK2tLVQqFWJiYnDjxg3s3bsXrq6u2LhxI3r37g0XFxcEBwcjJSWFVzemBunRowfi4uLwww8/wMLCAp6envDy8sLZs2fFjqYVbdu2xbfffovAwEDMnDkTs2fPRnl5udixiIiIiMhAcLIkERERERERERERERERkY5ZWFhAqVQiKioK165dQ3JyMhQKBbZv3w5PT084OjoiMDAQSUlJqKioEDsuNXNubm5ISkrCwYMHcePGDQwePBjvvfce8vPzxY72wkxMTBAWFoZdu3Zhx44dGDNmjEHsFxERERGJj5MliYiIiIiIiIiIiIiIiJqQiYkJPDw8EBkZiStXriAjIwN//vOfkZiYCC8vL9jZ2dWU8n748KHYcakZGz9+PH766Sfs3LkThw4dQvfu3REcHIy7d++KHe2F+fv7Iy0tDUVFRXBzc0NqaqrYkYiIiIhIz3GyJBEREREREREREREREZGIXFxcEBoaiqysLOTm5mLZsmXIy8vDpEmT0Lp1ayiVSsTExBjEBDjSPqlUCpVKhXPnzuGjjz5CVFQUnJycEB4erveTbXv37o2TJ09i6NChGD16NCIjI8WORERERER6TCIIgiB2CCIibZBIJGJHIDI4vr6+UKvVYscgLVCpVNi9e7fYMYiIiPQGT5dQfeLi4uDv7y92DCJqYrGxsfDz8xM7BhEZqd9++w3ffvstNBoNvvvuu5orUnp7e8Pf3x8dO3YUOyI1Q8XFxYiIiEBkZCS6dOmClStXwtfXV6+/RxEEAREREViyZAmmT5+OqKgoWFhYiB2LiIiIiPSLmpMlichgSCQSLFiwAO7u7mJHoadITU3FunXrEBsbK3YUeoa1a9eiU6dOnCxpIFQqFa5cuYL3339f7ChEes3f35/jDSIDVz1e5ekSqk/1ZEn+f8b4rF27FgA4njZC1Z95TpYkouaguLgYCQkJSEhIwIEDB1BWVgZ3d3colUr4+PigR48eYkekZuby5ctYuXIltmzZAjc3N0RERGDUqFFix3oh+/fvx5tvvgkHBwd8/fXX6Natm9iRiIiIiEh/cLIkERkOiUTCk9d6oPrLRR5+mj+VSgUAnCxpINieRNrB8QaR4eN4lZ6G7w/jxfG08eL4j4iaq/v37+Pw4cNQq9XYt28f7ty5A2dnZ6hUKiiVSri6uoodkZqR9PR0LFq0CEeOHIFCocC///1v9OvXT+xYz+38+fPw8fFBQUEBdu3aBYVCIXYkIiIiItIPaqnYCYiIiIiIiIiIiIiIiIio4SwtLaFUKhETE4ObN28iOTkZCoUCmzdvhpubGxwdHREYGIiUlBRUVVWJHZdE5urqisOHDyMxMRFFRUUYPHgwZs+ejfz8fLGjPZcePXogNTUVL7/8MsaPH4/w8HD+oImIiIiIGoSTJYmIiIiIiIiIiIiInuD777/HDz/8gDt37ogdhYioXiYmJvDw8EBkZCQuX76MtLQ0BAQE4LvvvoOnpyc6duyIgIAAaDQalJeXix2XRKRQKJCeno6dO3fi0KFD6NGjB4KDg3H37l2xozWalZUVYmNj8a9//QvLli3DtGnTcO/ePbFjEREREVEzx8mSRERERERERERERERPsGXLFgwbNgytWrXCSy+9hDFjxmDOnDn49NNPkZSUhCtXrogdkYiohlQqhaurK0JDQ3Hu3DlkZGRg4cKFyMvLw6RJk9CxY0f4+fkhJiYGJSUlYsclEUilUqhUKmRnZ2PVqlWIioqCk5MTwsPD9W4yrUQiQWBgIJKSknDkyBG4ubnh3LlzYsciIiIiomaMkyWJiIiIiIiIiIiIiJ5g+/btuHr1KhITE7Fo0SJ0794dOTk5WLVqFby8vNC5c2eYm5vDxcUFfn5+CA0NhVqtRnp6OsrKysSOT0RGzsXFBUFBQUhJScHFixcREhKCW7duYebMmWjfvj2USiWio6Nx48YNsaNSEzM1NUVgYCByc3Mxc+ZMhIaGol+/flCr1XpX0nrUqFFIS0tDy5YtMWzYMOzdu1fsSERERETUTHGyJBEZre3bt0MikdTcrKys6l3u119/xcSJE3H37l0UFRXVes6gQYPw4MGDOs/543ISiQRubm663iWtCA4ORmxs7BMfe3yfhg8f3iSZ2Fb1a45tRWTIjKFfIRKDsR2/G+LAgQPo2bMnZDLZE5d52jiAiPQX+8S6jKVPZNvX1dza3t7eHgqFAoGBgYiKikJiYiLy8/NRXFyMtLQ0REdHQ6lUAgDUajWmTp0KNzc3tGzZEk5OTvDy8kJgYCCio6ORkpKil+VOiUj/de3aFYGBgTV9WFRUFABg/vz5sLe3rynlzSvmGpfWrVsjLCwM2dnZGD16NKZOnQp3d3ccPXpU7GiN0rlzZ/z3v/+Fr68vfHx8EBwcjKqqKrFjEREREVEzw8mSRGT0Nm7cCEEQUFpaWuex06dPw83NDWPHjkXLli3Rtm1bCIKAU6dO1Ty+YMGCOs+rXi41NRVt2rSBIAhIS0vT+b5ow1/+8hcsXrwYy5cvr/NYWFgYBEGAIAgwMTFp8mxsq9qac1sRGSJj6FeImpoxHr+fJjc3FxMnTsTixYtx/fr1py77tHEAEekn9om1GVOfyLavTd/a3tbWFq6urggICEBYWBji4uKQmZmJsrIyZGRkYOfOnZg1axbs7Oxw7NgxvP/++/D09ISNjQ1at24NDw8PzJ49G+Hh4dBoNMjLy9O7q3kRkX5q27YtAgICoNFoUFxcjPj4eDg6OuKDDz5A586d4eLigtDQUGRlZYkdlZpIly5dEBUVhZMnT6JFixYYNWoUvLy8kJGRIXa0BjM3N8fWrVuxadMmrF27FhMnTsTt27fFjkVEREREzQgnSxIRPcHdu3ehVCoxZcoUzJ07t87jZmZmaNOmDaKiorBr1y4REuqGk5MT4uPjsWrVKsTFxYkdp0HYVvrTVkSGwlD7FaKmZKzH76dZvnw5RowYgfT0dFhbWz91WY4DiAwL+8S6jKVPZNvXZShtb2pqChcXF6hUKgQFBSEmJgZpaWm4d+9eTUnvkJAQuLi4IC8vr2ZCh5OTE2xtbeHm5lanpHd9VxglItIGS0tLKJVKxMTE4Pr160hMTIRCoUBUVBRcXFzg5OSEwMBApKSkcEK3EXBzc8Phw4eRmJiIwsJCDBo0CLNnz0ZBQYHY0Rps1qxZOHLkCH788UcMHTpUryZ8EhEREZFucbIkEdETREREoKCgAB988EG9j5ubm2PHjh2QSqWYPXs2cnJymjih7gwYMAC+vr5YuHAhKioqxI7zTGwr/WkrIkNhyP0KUVMx5uP3k2zduhXBwcFPLTf6OI4DiAwH+8S6jKVPZNvXZQxtX19J74KCgpqS3uvXr4dCoUBZWRm2bdtWp6S3UqlEcHBwTUnvkpISsXeJiAyIubk5FAoFIiMjcfXqVSQnJ0OlUuHgwYPw9PRE165dMXv2bGg0Gjx69EjsuKRDCoUCP/74I3bu3IlDhw6he/fuCA4Oxt27d8WO1iAjR47E6dOn8dJLL8Hd3R1qtVrsSERERETUDHCyJBFRPQRBwJYtWzBs2DDY29s/cblx48Zh2bJlKCkpgUqlMqhf+E+ePBlXrlzB/v37xY7yVGwr/WkrIkNjyP0Kka7x+F0/CwuLRj+H4wAi/cc+sX7G0Cey7etnDG3/JH8s6a3RaJCbm4v79+8jIyMDO3bswKxZs2Bra4ukpCQsWLAAnp6eaNmyZa2S3pGRkUhKSmJJbyJ6YVKpFB4eHggLC0NOTg4yMjLwzjvvID09HRMnTkTHjh0REBAAtVqN0tJSseOSDkilUqhUKmRlZWH58uWIioqCk5MTIiMj9eJHCu3bt0diYiLmzJkDf39/BAYG6kVuIiIiItIdTpYkIqrHmTNncP36dQwYMOCZy4aEhGDs2LH4+eefMW/evAat/+bNm/jb3/4GJycnmJqawtbWFq+++ir+85//1Cyzd+9eSCSSmtulS5fg7++PVq1aoU2bNvD29kZubm6ddRcWFmL+/Pno1q0bTE1N0a5dO/j4+OD06dMNfwEADBw4EADw3XffNep5TY1tpT9tRWSIDLVfIdI1Hr+1h+MAIv3HPlF79K1PZNtrj761fWOZmZnVW9L77t27yM3NrVPS+6OPPoKXl9cTS3pnZmaisrJS7N0iIj3k4uKC0NBQpKWlIS8vDx988AHy8vIwdepUtG/fvqaU9+3bt8WOSlpmYWGBoKAg5ObmYubMmQgKCkLfvn2hVqub/cR8mUyGsLAwxMTEYMuWLVAoFLhx44bYsYiIiIhIJJwsSURUj4yMDABAp06dnrmsVCrFjh070LlzZ2zZsgU7dux46vIFBQUYMmQIdu7cicjISBQVFeHkyZOwtLTEmDFjsGXLFgDA66+/DkEQMGnSJADAggULsGDBAly9ehWxsbE4cuQI3njjjVrrzs/Px5AhQxAXF4cNGzaguLgY33//PYqLi+Hu7o7U1NQGvwYvvfRSrdeiuWJb6U9bERkiQ+1XiHSNx2/t4TiASP+xT9QefesT2fbao29try0ymQyOjo51Snpfv34dxcXFSE5ORkRERK2S3v7+/ujbty8sLCzqLenNK8MRUUM5ODggMDAQKSkpKCgowKZNmwAAf/nLX9C2bVt4eHggMjIS165dEzkpaVPr1q1rrjQ6atQoTJ06Fe7u7khOThY72jO9+eabSElJwW+//QY3NzecOnVK7EhEREREJAaBiMhAABBiY2MbvPy2bdsEAMLGjRvrPBYRESEAED777LN6n3vq1CnBxsam1n2pqamCXC4XWrRoIfzyyy8197Vp06bWcm+//bYAQNi1a1et+x88eCDY29sLFhYWQkFBQc39kyZNEgAIGo2m1vK+vr4CAKGwsLDmvj//+c8CAGHHjh21ls3PzxfMzMwEV1fXJ70c9ZJIJEL37t3rfczExEQYNmxYo9YnCIIQGxsrNPbww7Z6Nl20la+vr+Dr69vo51HzxPbUHmPpV6h+jR1vUP14/H62l156STAxMWnQsk8bB1DjPc94lYyHLt4f7BOfrTn0iboYT7Ptn605tL2hjf8ePHggZGRkCHFxcUJISIigUqkEV1dXwdzcXAAgABDs7OwEhUIhzJo1S1i3bp2QmJgo5Obmih2diPREcXGxEBcXJ7z11luCtbW1IJVKBVdXVyEkJKTm2EWG49SpU8LLL78sABAUCoWQkZEhdqRnKioqEry8vARzc3Nh69atYschIiIioqYVxytLEhHV48GDBwAAuVze4OcMHz4ca9aswb1796BSqVBWVlbvcvHx8QCACRMm1LrfzMwMY8aMQVlZWb1lo4YMGVLr3507dwaAWr/M3bt3L6RSKby9vWst27FjR7i4uCA9PR1Xrlxp8D7JZLIn7kdzwbb6nT60FZEhM8R+hUiXePzWLo4DiPQb+0Tt0qc+kW2vXfrU9mJ6vKR3aGgo4uLikJaWhpKSkpqS3kFBQXB0dERmZiY++OCDOiW9AwICEB4ezpLeRFQvW1tbqFQqxMTE4MaNG9i7dy9cXV2xadMm9OnTBy4uLggODkZKSkqzL99Mz+bm5oYjR44gMTERhYWFGDRoEGbPno2CggKxoz1RmzZtcPDgQQQGBuLdd9/F7NmzUV5eLnYsIiIiImoinCxJRFQPc3NzAMCjR48a9bz58+fD398fGRkZmDt3bp3HHz58iDt37sDc3BzW1tZ1Hu/QoQMA1HsiwcbGpta/TU1NAQBVVVW11l1VVQUbGxtIJJJatx9//BEAcP78+QbvT0VFBSwsLBq8vBjYVr/Th7YiMnSG1q8Q6RKP39rFcQCRfmOfqF361Cey7bVLn9q+OaqvpHdKSgru3LlTU9I7PDwcCoUCt27dQnR09BNLesfExCA9PZ0lvYkI5ubmUCqViIqKwtWrV5GcnAyFQoEdO3bA09OzppR3UlISKioqxI5LL0ChUODHH3/Ejh07cOjQIXTv3h3BwcEoKSkRO1q9TExMEBYWhvj4eHz11Vd45ZVXkJ+fL3YsIiIiImoCMrEDEBE1R3Z2dgCAO3fuNPq5W7ZswenTp/H555/XfPFRzczMDDY2Nrhz5w5KSkrqfGlx/fp1AL9fjaGxzMzM0KpVK5SWlqKsrAwy2Yt18Xfv3oUgCDWvRXPFttKftiIyBobSrxDpGo/f2sNxAJH+Y5+oPfrWJ7LttUff2l7f2NrawsPDAx4eHrXuv3PnDi5cuIC8vDxkZmYiKysLSUlJiIyMrLlyqp2dHVxcXODo6AhnZ+eavzs6OoqxK0QkIhMTk5q+JDIyEpmZmVCr1VCr1Vi/fj3atGmD1157DSqVCmPHjoWZmZnYkamRpFIpVCoVJkyYgE8++QSrV6/G559/jqVLl2LOnDnNZtzwuEmTJuGHH37A5MmT4ebmBrVajREjRogdi4iIiIh0iFeWJCKqR9++fQHgucpGWVlZYc+ePWjRogU2bNhQ5/HJkycDAPbv31/r/ocPH+Lw4cOwsLDAuHHjniM14OPjg4qKChw7dqzOY+Hh4ejSpUuDf6F79epVAP/3WjRXbCv9aSsiY2Ao/QqRrvH4rT0cBxDpP/aJ2qNvfSLbXnv0re0NhY2NDVxdXeuU9L579y5yc3Oxb98+BAYG1pT0Xr58eU1J79atW7OkN5GRc3FxQWhoKDIzM5Gbm4vly5cjLy8PkyZNQuvWraFUKhETE/NcPyogcVlaWiIoKAi5ubl45513EBQUhL59+0KtVosdrV69evXCiRMnMGzYMIwaNQrh4eFiRyIiIiIiHeJkSSKiegwYMADt27fHmTNnnuv5Li4uiIqKqvex1atXw8HBAQsWLEBCQgJKSkqQk5ODadOmIT8/H5GRkTUlsRpr9erVcHJywjvvvIODBw/WlEqKiorChx9+iDVr1tT69eabb74JiUSCixcv1lnX6dOnAQBjx459rixNhW2lP21FZCz0pV8hEhOP39rDcQCR/mOfqD361iey7bVH39re0Mnlcjg6OkKpVCIoKKimpPfdu3drSnqHhYVh5MiRyM/Pr1XS29LSst6S3vfu3RN7t4hIhxwdHREYGIiUlBT8+uuvWLt2LQDg3XffRYcOHeDl5YXIyEiWSdYzbdq0QVhYGHJycjB06FD4+/vD3d0dycnJYkero2XLltizZw9WrlyJJUuW4K233sL9+/fFjkVEREREuiAQERkIAEJsbGyDl9+2bZsAQNi4cWO9jy9ZskSQyWTC1atXa+4rLCwUANS6ubq6PnEbf/3rX4U2bdrUub+oqEhYsGCB4ODgIMjlcsHGxkYYN26ccPjw4ZplUlNT62xr6dKlNfv6+G3ChAk1z7t586bwt7/9TXB0dBTkcrnQrl07YezYsUJiYmKdHK+88opgZWUlVFRU1HlMpVIJL730klBeXl7vvpmYmAjDhg174r4/SWxsrNDYww/bSpy28vX1FXx9fRv9PGqe2J4vztD6FXo+jR1v0JMZ+/G7PhqNps62q2+bN2+u9znPGgdQ4z3PeJWMh67eH+wT62pufaKuxtNs+7qaW9tz/Nc0bt26JaSlpQlxcXFCSEiIoFKpBGdnZ8HExKSm/e3s7ASFQiHMmjVLWLdunZCYmCjk5+eLHZ2IdOjmzZvCl19+KahUKsHKykqQSqXCyJEjhbCwMCE7O1vseNRIP/zwg/Dyyy8LAARvb28hJydH7Ej12r9/v2BraysMGjRIuHjxothxiIiIiEi74iSCIAhPnU1JRKQnJBIJYmNj4efn16Dlt2/fjrfeegsbN27Ee++9V+fxO3fuwMXFBd7e3ti0aZO244ru9u3bsLe3x/Tp07F58+Zaj505cwaDBg3Czp07MXXq1HqfL5PJ4ObmhhMnTjRqu3FxcfD390djDj9sK3HaSqVSAUCzLY9CjcP2JNKOxo436MmM+fitLQ0ZB1DjPc94lYyHrt4f7BNfnK77RF2Np9n2L07Xbc/xn7gePXqEy5cvIzMzE1lZWcjLy0NmZibOnDmD0tJSAICtrS0cHR3h7OwMFxeXmr/36dMHUimLaxEZirKyMiQlJUGtVkOj0eD27dtwdnaGSqWCUqmEq6ur2BGpgZKSkrBw4UL88ssvmDFjBlasWIGOHTuKHauWCxcuwMfHB9euXcOuXbvg5eUldiQiIiIi0g416/ARET2BjY0NNBoNvLy80K9fP8yZM0fsSFojCALmz5+Pli1b4p///Getx/Ly8uDj44PFixfrzZfubCv9aSsiIqJqxnr81haOA4gMC/vEF6PPfSLb/sXoc9tTw1SX9K4u6/24a9eu1ZpAmZWVhWPHjiEvLw8AYGpqiu7du9eaQOni4oI+ffrA0tJSjN0hohdgYWEBpVIJpVKJyspKpKamQq1WY/PmzVixYgW6deuGiRMnQqVSYcSIEZws3YwpFAr89NNP2LNnD/7xj39gx44dmDt3LpYuXQpra2ux4wEAunfvjuPHj2PmzJl49dVXsWrVKixatAgSiUTsaERERET0gvg/BSIyen/9618hkUhgZWVV57FBgwYhLS0NBw8exN27d0VIpxvXr19HXl4eDh8+XOcXm1FRUVi1ahVWrVpV53nBwcGQSCSQSCSorKxsqrg12Fb601ZEREQNYYzHb2152jiAiPQT+8Tnp+99Itv++el729OLsbe3h0KhwKxZsxAZGYnExETk5ubi1q1bSEtLw+bNm2smWGo0Grzzzjtwc3NDixYtYG9vDy8vLwQGBiI6OhpJSUm4fv26yHtERA1lYmICDw8PREZG4vLly0hLS8Of//xnHDp0CJ6enujQoQMCAgKg0WhQXl4udlyqh1QqhUqlQlZWFpYvX45Nmzahd+/eiI6ORkVFhdjxAABWVlaIjY3Fhg0bsHz5ckyePNmgxmpERERExopluInIYLAskn5gWUP9wbLNhoXtSaQdHG8QGT6OV+lp+P4wXhxPGy+O/wzHH0t6V/957tw53Lt3D0Ddkt7Vf3br1o1XqSPSE5mZmUhISIBGo8Hx48dhaWmJl19+GSqVCpMnT242Vy6k2goLC/Hhhx8iKioKPXv2REREBF577TWxY9U4evQo/Pz8YGtri6+//hp9+vQROxIRERERPR+W4SYiIiIiIiIiIiIiIsPW2JLeSUlJyM/PBwCYmZnBycmpTklvZ2dnWFhYiLE7RPQELi4ucHFxQVBQEH799Vfs3bsXCQkJmDlzJmbPng0PDw94e3tj6tSp6NChg9hx6f9r164dPvnkE8yfPx+LFy/GhAkToFAosGbNGgwYMEDsePjTn/6EtLQ0TJkyBcOHD8cXX3yByZMnix2LiIiIiJ4DJ0sSEREREREREREREZHRsre3h729fZ37b926VWsCZV5eHjQaDdasWYPKykrIZDJ06dKl1gRKR0dH9O/fH+3btxdhT4jocV27dkVgYCACAwNx8+ZN7N+/H2q1GkFBQVi4cCGGDx8OpVKJKVOmoHv37mLHJQA9evTA7t27cfLkSfz973/H4MGDMWXKFHz88cfo2rWrqNk6deqEo0ePYu7cuZgyZQoWLVqEjz76iFceJiIiItIznCxJRERERERERERERET0B7a2tnB1dYWrq2ut+8vLy3H+/PlaV6M8duwYtm7dWquk9+MTKFnSm0hcbdq0QUBAAAICAnD//n0cPnwYarUaq1evRnBwMJydnaFSqaBUKut85qnpDRs2DMnJydBoNHj//ffh7OyMefPmYcmSJWjZsqVouczMzLB582YMGTIESe7GgwAAIABJREFU8+bNw9mzZ7F9+3bY2tqKlomIiIiIGoeTJYmIiIiIiIiIiIiIiBrI1NS0ptTvH1WX9H78apT79u1DQUEBgNolvf84mZIlvYmahqWlJZRKJZRKJR4+fFgzKS86OhorVqyAo6MjvL29oVKpMHLkSEgkErEjGy2lUonx48djw4YNCA0NxdatW7Fs2TLMmTMHMpl4X3PPmjULffv2hUqlwtChQxEfH4++ffuKloeIiIiIGo4/XyQiIiIiIiIiIiIiItICe3t7KBQKBAYGIioqComJicjPz0dxcTHS0tIQHR0NpVIJAFCr1Zg6dSrc3NzQsmVLODk5wcvLC4GBgYiOjkZKSgru3r0r8h4RGTYzMzMoFApERkbiypUrSE5OhkqlwrfffgtPT0906NABAQEB0Gg0ePTokdhxjZJcLkdgYCByc3Mxc+ZMBAUFoV+/flCr1aLmGjFiBE6fPo3OnTvD3d0dcXFxouYhIiIioobhlSWJyKCkpqaKHYGeobqNeOKg+bty5Qo6deokdgzSoitXrvCzR6QFHG8QGTZ+xqkhOKYyPleuXAHAtiei59fYkt5btmzB/fv3a55bX0lvBwcHXvGOSIukUik8PDzg4eGBsLAwZGZmQq1WIyEhARMnToStrS0UCgW8vb3h4+MDKysrsSMbldatWyMsLAwzZ87E0qVL4e/vj6ioKKxZswYDBw4UJVO7du1w6NAhLFu2DP7+/jh8+DA+/fRTyOVyUfIQERER0bNJBEEQxA5BRKQNPDFIpH2+vr6i/0KXtEOlUmH37t1ixyAiItIbPF1C9YmLi4O/v7/YMYioicXGxsLPz0/sGGSE6ivpffbsWVy/fh0AYGNjg+7du9eaQOno6AgXFxeYm5uLnJ7IsFy6dAnffPMNEhIS8P3330Mul2PMmDFQKpV4/fXX0b59e7EjGp2TJ09i4cKFSE1NxZQpU/Dxxx+ja9euouXZsWMHZs2ahSFDhiA2NhYdOnQQLQsRERERPZGakyWJiIiIiIiIiIiIiIj0xK1bt2quQvn4ZMpLly6hqqoKcrkcnTt3rnM1ygEDBsDa2lrs+ER6r6ioCAcOHIBarcahQ4dQWVmJ4cOHQ6VSwdfXFy+99JLYEY2GIAjYvXs3goODUVBQgHnz5mHJkiVo2bKlKHlOnz4NHx8fPHr0CHv27MHQoUNFyUFERERET8TJkkRERERERERERERERPru4cOHuHDhQq2S3llZWcjKykJZWRmA2iW9H59MyZLeRM/n3r17OHLkCNRqNfbu3YuSkhI4OztDpVLB398fffr0ETuiUSgvL8fGjRsRGhoKmUyGZcuWYe7cuTAxMWnyLDdv3sS0adPw3//+F5999hlmzpzZ5BmIiIiI6Ik4WZKIiIiIiIiIiIiIiMhQVVRU4Lfffqs1gTIvLw8///wzbty4AaD+kt7Ozs7o3bu3KJONiPTRgwcPkJKSAo1Gg9jYWFy/fh2Ojo7w9vaGSqXCyJEjOSlZx4qLixEREYF169bB0dERK1asgEqlavIclZWV+Oc//4kPP/wQf/nLX/DJJ5/A1NS0yXMQERERUR2cLElERERERERERERERGSMbt26VWsCZfXfL168CEEQnljSe+DAgbCyshI7PlGzVVlZidTUVCQkJGDPnj24cOECunTpgvHjx8Pb2xvjx4+HXC4XO6bBysnJwbJly7B7926MGTMGa9aswYABA5o8x759+xAQEIC+ffsiLi4O9vb2TZ6BiIiIiGrhZEkiIiIiIiIiIiIiIiL6P4+X9P7jZMoHDx4AAOzs7GpNoKz+u6Ojo8jpiZqfzMxMqNVqJCQkID09Ha1bt8aECROgVCrx2muvoUWLFmJHNEgnTpzAwoULceLECUyfPh3h4eGws7Nr0gzZ2dnw8fFBYWEhYmNj8fLLLzfp9omIiIioFk6WJCIiIiIiIiIiIiIiomerr6R3ZmYmzp49i7t37wIAWrVqBScnpzpXo2RJb6Lf5eXlQaPRQK1W4/jx47CwsMArr7wClUqFSZMmwcbGRuyIBkUQBOzevRtBQUG4fv065s2bh6VLl8La2rrJMpSUlODtt9/Gvn37sHLlSgQFBTXZtomIiIioFk6WJCIiIiIiIiIiIiIiohfT2JLe1X/26tWLJb3JaBUWFuLgwYNQq9U4dOgQKisrMXz4cKhUKqhUKpZt1qLy8nJs3LgRoaGhsLS0REhICGbOnNlkk7gFQUBERASWLFmCN954A9HR0bC0tGySbRMRERFRDU6WJCIiIiIiIiIiIiIiIt24c+cOLly4UGsCZUNKeru4uDR5uVwiMd26dQtJSUnQaDSIj4/H/fv3MWjQIHh7e+ONN95Ar169xI5oEIqLixEREYG1a9fCyckJERER8Pb2brLtHzx4ENOnT0fXrl3x9ddfw8HBocm2TUREREScLElERERERERERERERERN7NGjR7h8+XKdCZQ///wzSkpKAAC2tra1JlCypDcZi7KyMiQlJSEhIQF79+7FjRs34OzsDKVSCW9vb4wcORISiUTsmHotJycHy5Ytg1qthkKhwJo1azBgwIAm2faFCxfg4+ODa9euYdeuXfDy8mqS7RIRERERJ0sSERERERERERERERFRM/J4Se/HJ1NWl/Q2NTVFp06d6pT07t27N1q0aCF2fCKtqqysRGpqKtRqNfbs2YOrV6+iW7dumDhxIpRKJUaPHg2ZTCZ2TL114sQJLFy4ECdOnMD06dMRHh7eJFe1ffDgAd577z1s374dq1atwqJFizgBloiIiEj3OFmSiIiIiIiIiIiIiIiImr/bt28jNze3VknvzMxMZGdno7KyEkD9Jb379u2Ljh07ipyeSDsyMzOhVqsRFxeHX375BW3btsWrr74KlUqFsWPHwszMTOyIekcQBOzevRtBQUG4ceMG5s6di6VLl8La2lrn246OjsbcuXPx6quvIiYmBjY2NjrfJhEREZER42RJIiIiIiIiIiIiIiIi0l9PKul95swZlJaWAnhySe8+ffpAKpWKvAdEzycvLw8ajQZqtRrHjx+HhYUFXnnlFahUKrz++uto2bKl2BH1Snl5OTZu3IiQkBC0aNECISEhmDlzJkxMTHS63aNHj8LPzw+tWrVCfHw8+vTpU+9yiYmJGD16NORyuU7zEBERERkwTpYkIiIiIiIiIiIiIiIiw3Tt2rVaEyir/56XlwcAMDU1Rffu3etcjbJPnz6wtLQUOT1Rw/3222/49ttvodFo8N1338HExAQeHh7w9vaGv78/r67aCDdv3sTHH3+MtWvXonv37oiIiMCECROe+byKiornLol+5coV+Pr6IisrC19++SUmT55c6/HTp0/D3d0dy5cvx5IlS55rG0RERETEyZJERERERERERERERERkZKpLev/xapT1lfR+/GqU/fr1Q4cOHUROT/R0xcXFSEhIQEJCAg4cOICysjK4u7tDqVTCx8cHPXr0EDuiXsjOzsby5cuhVquhUCjwr3/9C/3793/i8h9++CEsLCzwj3/847m29/DhQ8ydOxdbt27FokWL8NFHH0EqlaK4uBgDBgzA1atXIZfLkZGRwTYkIiIiej6cLElEREREREREREREREQE1C3pXf3nuXPncO/ePQB1S3pX/9mtWzeW9KZm5/79+zh8+DDUajX27duHO3fuwNnZGSqVCkqlEq6urmJHbPZSU1OxcOFCnDx5EtOnT0d4eDjs7OxqLZOfnw8nJyc8ePAAu3btgr+//3NvLzo6GvPmzcOYMWOwbds2TJs2Df/5z3/w6NEjyOVyDB06FMnJyZBIJC+6a0RERETGhpMliYiIiIiIiIiIiIiIiJ6lvpLemZmZyM/PBwCYmZnBycmpTklvZ2dnWFhYiJyeCKisrERqairUajV2796Na9euwcHBAUqlEiqVCiNGjGj0hF9fX18sWrQIQ4cO1VHq5kEQBOzevRuLFi1CYWEh5s6di6VLl8La2hoA8M4772D79u149OgRZDIZkpKSMGrUqOfeXmpqKnx9fVFeXo5bt27VXPEWACQSCT7//HO8/fbbL7pbRERERMaGkyWJiIiIiIiIiIiIiIiIntetW7dqTaD8Y0lvmUyGLl261JpA6ejoiP79+6N9+/aiZK6srISJiYko26bmoaqqCj/99BM0Gg2++uorZGdno127dhg/fjxUKhXGjRsHU1PTp67j8uXL6Nq1K2QyGdavX4/33nuvidKLp6ysDOvXr8fq1avRokULhISEYMiQIXBzc0NVVRUAQCqVwsLCAsePH39q2e5n+eKLLzBjxow690skElhbW+P8+fOi9SFEREREeoqTJYmIiIiIiIiIiIiIiIi0rby8HOfPn69zNco/lvR+fAJlU5X0jo2NxZdffonw8HD069dPZ9sh/ZGZmYmEhARoNBocP34crVq1gkKhgLe3NyZPnlxzBcXHffLJJ/jb3/6GiooKSCQS+Pr6YsuWLWjZsqUIe9C0bty4gZCQEGzZsgXt2rVDUVERHj16VPO4TCZD69atkZ6ejk6dOjV6/dnZ2Rg8eDDKyspQ39f5crkcvr6+2Llz5wvtBxEREZGR4WRJIiIiIiIiIiIiIiIioqZUXdL78atRZmRkoKCgAEDtkt6PT6Z0cXGBubn5C28/NDQUK1asgEQiwbRp07Bq1Sp07dr1hddLhuHXX3/F3r17kZCQgO+//x4ymQwKhQJKpRKTJk1Chw4dAACenp44fvx4zRUV5XI52rdvj6+//trgy3JX27BhA+bMmVPvYzKZDN27d8eJEydgY2PT4HWWlJTA1dUVFy9eREVFxVOXTUhIwIQJExqVmYiIiMiIcbIkERERERERERERERERUXPwpJLe586dQ1VVVb0lvZ2dndG/f/9GXc3Pz88Pe/bsqVknAMyYMQP//Oc/aybCEQFAQUEB9u3bh/j4eBw5cgRVVVUYPXo0vLy8sHjx4pqJktVkMhkkEgk+/vhjBAYGipS6aVRUVMDZ2Rl5eXmorKysdxm5XA53d3ckJiY+s6w5AAiCgMmTJ+Obb7555rJSqRT29vbIzs6GpaVlo/MTERERGSFOliQiIiIiIiIiIiIiIiJqzp5U0vuXX37B/fv3ATy5pLeDgwMkEkmt9fXu3RvZ2dm17pPL5ZDJZJg/fz6WLl1ab9llMm7379/H4cOHoVarceDAAdy6davOZMlqEokESqUSX375JVq1atXESZvG+vXr8f777z/xNahmYmICf39/bN++vc5n8Y8ePnyI7du3Y/v27Th69CikUimqqqqeuA2ZTIYFCxbg448/fu79ICIiIjIinCxJREREREREREREREREpI8qKipw8eJF/PLLLzh37hyys7ORlZWFc+fO4fbt2wAAGxsb9OrVC87Ozujduzd69eoFf39/lJeX17tOmUwGa2trBAUF4f3332/Q1fDI+EyYMAHffffdE6+oCBh2We7bt2/DwcGh5nP2LFKpFMuXL0doaGiDt3Hz5k3s378fn3/+OY4ePQqZTIaKigr88et9qVSKU6dOYfDgwY3ZBSIiIiJjxMmSRERERERERERERERERIbmjyW9q/+8dOnSM6+EB/x+NbwuXbogPDwcvr6+z7wiHhmP0tJStGnT5okTbh9nqGW5v/nmGyxduhTZ2dmoqKiAVCqFXC5HeXl5ncmM1SQSCbZu3YoZM2Y0enuXL1/G119/jR07duDUqVOQy+V49OgRgN9f4549e+LMmTOQyWQvtF9EREREBo6TJYmIiIiIiIiIiIiIiIiMxZ49e+Dr69ugZaVSKQRBwMCBA/Hvf/8bo0eP1m040gu7d++Gn5/fEycFPsmUKVPw+eefo2XLljpK1vQePXqE7OxsnD17Fj///DPOnDmDM2fO4Nq1awB+v7qmRCKpmVhqYmKC/fv3Y9y4cc+9zXPnzuGrr77Ctm3bkJeXV1Oq+9///jfef/99rewXERERkYHiZEkiMhz8VSuR9vn6+kKtVosdg7RApVJh9+7dYscgIiLSGzxdoltxcXHw9/cXOwYRkUGLjY2Fn5+f2DGeC8/zEREREREREdGLquc8v5rX4SYig7JgwQK4u7uLHUM0a9euBQD+cpC0ovr9RIZj+PDh7B+IqFH8/f2NfnxFxic1NRXr1q0TO4bRiI2NFTsCkdZV9yN8f5OYDGFCOsehRLoTFRWF//73v6isrKzzmImJCQRBqCnTbWtrCwcHBzg4OKBLly7o2rUrOnbsyEnNRi46OhoPHz6Eubk5JBIJLC0tAQCWlpaQSCQwNzeHiYkJTE1NYWpqChMTk1rLyuVydO7cWeS9EEdhYSEuX76MkpIS/OlPf9LaZ0kQBOTk5KC0tBSurq5aWWdT4fiZiIiItO1p5/k5WZKIDIq7u7ve/mJeG6qvAGjMrwFpD68oaXg6derE/oGIGsXf39/ox1dknDhZsumwfyFDtW7dOr6/SVSGMFmS41Ai3VmzZg0qKyshl8tRUVEBQRBgbm6O3r17Y+jQoejfv3/NzcbGRuy41AyxfyZt4/iZiIiItI2TJYmIiIiIiIiIiIiIiIiMXGVlJZRKJQYOHIj+/ftjwIABcHJyglQqFTsaERERERGRTnGyJBEREREREREREREREZGRSE9PFzsCERERERGRKPgTMSIiIiIiIiIiIiIiIiIiIiIiIiIyaJwsSUREREREREREREREREREREREREQGjZMliYioQaysrCCRSGrd1qxZI3as52JI+0LUHMTGxmLgwIGwsLCo+UxlZGSIHYvI6AiCgGPHjmHOnDno2bMnzMzM0L59e3h4eGD79u0QBKFJclRWVmLTpk0YMWIEbGxsIJfLYW9vj9deew2ffvopLl26VLPsmjVravqNTp06NUm+ppSWloa3334b3bp1g7m5OVq1aoUhQ4bgww8/xO3bt194/c19TKOt9v3qq69q1mNubq7FhESGr6n7WX3v1w8cOICePXtCJpM1+babe58ulubwuuj7+5qI6HE8h6NdYo4diIjIeA0cOLDO/5Oedlu5cmW9/7d60m3Lli11tsnznDzPSWRIOFmSiIgapLS0FD/99BMAYNKkSRAEAX//+99FTvV8DGlfiMR27NgxvPHGGxg7diwKCwtx4cIFfoFIeqO0tBQ9evSAt7e32FG0Ijs7Gx4eHsjJycHu3btx584dnDhxAl26dMFbb72Ff/zjH02S46233sKcOXPw+uuvIzMzEyUlJUhOTsagQYMwf/58uLm51Sz797//HYIgYMCAAXXW86LtI3b7Ll68GMOHD4etrS0SEhJw+/ZtXLx4ESEhIYiPj0fPnj1x7NixF9pGcx/TPK19G2Pq1KkQBAFjxozRUjLSV2J/rvWRtj6HzXV72pKbm4uJEydi8eLFuH79uigZmnufLpbm8Lro6/uaiOiPeA5He5rD2IGIiIybWq2GIAg1t9mzZwMADh48WOt+f39/APX/36q+26hRo+psi+c5eZ6TyNBwsiQRERkkKysreHh4iB2DSO8967NU/R/ywMBAWFlZwcnJCZcvX0bfvn2bMKXhYN+lfU97TQVBQFVVFaqqqhr1vOZMJpMhLi4O/fv3h7m5ORwdHfHFF1+gTZs2+PTTT/Hw4UOdbv/UqVPYtWsXZs6ciUWLFqFTp04wNzeHk5MTVq1ahb/+9a8NXtfT2qcpnv8iVq5cibCwMHz22WdYu3Yt+vbtC3Nzc9ja2sLb2xvHjh1Dly5d8Oqrr+LcuXNNno9IX2nzc62v/TzpxvLlyzFixAikp6fD2tpa7Dhawfc4EZHx4TmchtHGMdIQxw5ERET14XlOIjJEvC48ERER0f9j787Doyrv//+/JpkkJCEEiBJCiBBwQalEjAgqFBRKpKxyJVCLaFsX6gYI9IsLimupQotaFbdqrVtD6Ac0KCpQ8ZKtRtkUWWQTgYSdkEASSHL//vCXkXEmyczkTGbJ83Fdcyln7nPOfc77Pvd9n3vunAOf/fDDD5KkpKSkAOcE8F5CQoK2b98e6GxYpkuXLjp9+rTL8ujoaKWlpWndunUqLy9XTEyM3/KwceNGSdIFF1zg9vtRo0YpNzfXo201ND6Biu+2bdv0yCOP6NJLL3X8RffPxcXFafbs2frlL3+p8ePH65NPPmnkXAKhKdzqbQSPf/zjH4qNjQ10NgAA8CvGcKxD3wEAEEjr1q3zOO2///1vr7a9bNkyx/8zzgkgXPFkSQAAAPisqqoq0FkAUI9jx47pu+++U/fu3ZWYmOjXfSUnJ0uSFi9e7Pb7vn376tChQ37NQ6C9+OKLqqysVE5OTp3p+vTpo3bt2mnx4sXasWNHI+UOAOAOkx0AAE0BYzjWoe8AAAg3d911lyZOnOi0jHFOAOGKyZIA4KHDhw9r0qRJ6ty5s2JiYtS+fXsNGDBA//znP1VWVqZZs2bJZrPJZrOpffv2KigoUP/+/ZWQkKC4uDhdffXVWrFiRaAPw3ILFixwHLfNZtOuXbs0evRotWzZUklJSRoyZIjT01+8PU+PP/64I/2Zr0f56KOPHMvPOussl+2fOHFCK1ascKSx231/mHJlZaVyc3P1q1/9Sm3btlVsbKwuvvhiPfPMM45XAB47dszpPNhsNj3++OOO9c9cnp2d7dj2wYMHNX78eHXs2FHR0dE6++yzNXLkSKe/Cvv5Od6yZYtGjRqlpKQkx7Jwn3iCxlfftVRTLt977z1JPw4S22w29erVq1Hyd2adHB0drVatWmnQoEH69NNPXY7B23rZyuvSk/rjzLzWV3d5ctye5q2iokIPPfSQunTpori4OLVu3VpDhw7V+++/3+g/oGzevFkjRoxQYmKi4uLidPnll2vhwoUaMGCAI8+33HKLI70nMfK0DNd8ysvLPVrPmzz8fB/ff/+9Ro8erYSEBCUlJWns2LE6evSodu3apaFDhyohIUEpKSm69dZbVVJS0uDzevz4ca1YsULDhg1T27Zt9a9//avB26xPnz591LZtW3388ccaNGiQli1b5tPrcmuLT436+mW1re9tv6WGN2X0s88+kyRlZGTUe5w1aT7//PNG6Ut6Wif5q+xu3rxZgwcPdpzH2o7pzPMdHx+vPn36aPny5Q06JoQ+q65rK+v5Gv5oxxrrHsCTvoUvaX/urbfecrlfuuuuu3y61+OemzJeH8o1gKbGX2M49d13uUvn6ViFp/dinuTB6rEXAADwI8Y5GecEwpYBgDAhyeTm5vpl24WFhSY9Pd20bdvW5Ofnm+PHj5uioiLz2GOPGUlm9uzZjrQZGRkmPj7eXHHFFWblypWmtLTUFBQUmG7dupno6GizbNkyv+TRGGOys7NNdna237a/du1aI8kMHz7c5bvhw4c7vqs57sWLF5vY2FjTo0cPl/Tenqf4+Hhz1VVXuWwnMzPTJCUluSyvLb0nx/Jz+fn5RpL585//bI4cOWIOHjxonn32WRMREWGmTJnilDYrK8tERESYbdu2uWzniiuuMG+//bbj3/v27TMdOnQwycnJ5oMPPjAlJSXmm2++MX379jXNmjUzK1eudFq/5hz37dvXfPrpp+bEiRNm9erVJjIy0hw8eLDe4/CWv8sTGpev8azvWqopl2VlZQ3Jnldq6uTk5GSTn59viouLzZYtW8zIkSONzWYzr7zyilN6b+obq69Lb+oPY+o+394ed315u+WWW0xiYqL55JNPzMmTJ01RUZGZMmWKkWQ+/fRTH6Pjve+++860bNnSpKammk8++cRxzgcMGGDOPvtsExMT45Te2xj5WobrWs/XcjJy5Ejz5ZdfmtLSUvOvf/3LSDKDBg0yw4cPN2vXrjUlJSXmxRdfNJLMPffc481pdFHTR5Fk+vXrZzZs2ODTdnzpX33++ecmLS3Nsf82bdqYMWPGmHfeececOHHC7ToZGRkmNTXVZbm7+HjTL6stvt70W7wtoykpKUaS+d///lfvubrhhhscdcSZ58KbPpK/+jRnnqeGlt2MjAyTmJhorr76arN8+XJTUlJS6zG5O98bNmwwAwcONB07dnQ5394ekydyc3MNwyX+5+t5tuK6Nsa6et7f7ZhV9wDu6llv+ha+9L/O3F9lZaWZNGmS+dWvfmWOHDnilNbbez1/33OnpqaayMjIBm3D1/Jt5T13OJVxb9o6yvVP/DlO1hhCPf9AIFg5huPpfZevYxWetGee5sHKsRdfWNF3AJo67sOBhhs3bpyRZBYtWlRrmpp7q9o+EyZMcErPOGfoj3MCTVkd/Yu59DoAhA1/DqL+7ne/q3X71157rctkSUlm7dq1Tuk2bNhgJJmMjAy/5NGY4JgsmZ+f75InSS4/5Hl7ngI9WbJfv34uy2+44QYTFRVliouLHcs+/vhjI8nccccdTmmXL19uUlNTzalTpxzLbrrpJiPJaQKlMT8OBMbExJjMzEyn5TXn+MMPP6w3z1ZgsmR4CafJkjV18rvvvuu0vLy83LRr187ExsaaoqIix3Jv6hurr0tv6g9j6j7f3h53fXlLT083V155pcvy888/v1EnS+bk5BhJZt68eU7LDxw4YOLi4lwGDLyNkT8mS/paTj744AOn5V27djWSzGeffea0PD093VxwwQW15tlTFRUVZtOmTeaPf/yjiYyMNI8++qjX2/C1f1VeXm7eeOMNM3z4cJOQkOAYcEtKSnIpw8Z4N1nSm35ZfZOqPOm3eFtGawYRv/jiC3enxknNIOKMGTMcy7ztI/mrT2OMdWW35phWrVpV7zHVdr737t1rYmJi3A4ienNMnuBHmsbhr8mSnt6PWFXP+7sds+oewF09603fwpf+V83+jh49arKyssyECRNMZWWlS958mVTmz3vuYJ8s2RTLuDdtHeX6J6E+2TDU8w8EgpVjOJ7ed/k6VuFJe+ZpHqwce/EFkyWBhuM+HGg4byZLuru3uvPOO2udLMk4509CbZwTaMrqmizJa7gBwAPz58+XJA0aNMgx5L/oAAAgAElEQVTlu0WLFmnixIlOy+Lj43XJJZc4Lbv44ovVrl07rV+/XoWFhf7LbID16NHD6d9paWmSpH379rmkDZXzNGTIELev4MrIyNDp06e1ceNGx7KBAwfq4osv1j//+U8dPnzYsXzmzJm6++67FRUV5Vi2YMECRUREaMiQIU7bbdu2rbp27aqvvvpKe/bscdnv5ZdfbsVhASGrpk4ePHiw0/KYmBj1799fZWVl+vjjj52+87S+sfq69Kb+qI8vx11X3q699lqtXLlSt912m1avXu149faWLVvUr18/j/PVUB999JEkKSsry2n52WefrS5durik9zVGVvI1D5dddpnTv9u1a+d2eWpqqtt201vR0dHq0qWL5syZo2HDhumhhx7SkiVLGrxdT8TExOjGG2/UggULdOTIES1dulS/+c1vdPjwYd1www1au3atz9v2tl9WF0/6Ld6W0Zq4ntkPqE1Nmpp1avirj+RrnWRF2W3WrJl69uzptMzdMdV2vtu1a6fzzz/fsmNC+PLmfqQ23tTzjdWO+eMewJu+ha/9kC1btqhnz56KiIjQ008/rcjISEvyHir3kv5AGa8b5RoArOHpfZevdakn7ZmneeCeAAAA/2Cck3FOIFwxWRIA6lFRUaHi4mI1a9ZMCQkJHq3TsmVLt8vbtGkjSTpw4IBl+Qs2iYmJTv+Ojo6WJFVXV7ukDZXzVFxcrIceekgXX3yxWrVqJZvNJpvNpj/96U+SpJMnTzqlnzhxok6ePKkXXnhBkrR161b997//1W233eZIU1OuqqurlZiY6NhmzWfNmjWSpO+++84lP/Hx8f46VCDo1VcnJycnS5KKioqclntS3/jjuvS2/rD6uOvK2/PPP69//etf2rFjh/r3768WLVro2muvdfwY0RgqKipUUlKiZs2aqXnz5i7ft2rVyiW9rzGyMs++5qFFixZO/46IiFBkZKTi4uKclkdGRrptNxti6NChkqSFCxdaul1P2O12XXPNNXr33Xc1depUVVVVad68eT5ty5d+WV3q67d4W0YlqW/fvpKkdevW1bv/9evXS5LLBGV/9ZF8rZOsKLtJSUmy2Wwuy39eD9d1vmvSWnFMCF/e3I+4400935jtmNX3AN70LXzthxw9elQjRoxQ+/bttWjRIr311luW5T9U7iX9gTJe/7FRrgGgYTy972rIWIUn92Ke3vtxTwAAQMM999xzevrpp52WMc7JOCcQrpgsCQD1iImJUWJiosrLy1VSUuLROocPH5YxxmV5TYfPXQeoKfLmPEVEROjUqVMuaY8dO+Z22+46qb4aOnSoHnvsMd16663aunWrqqurZYzR7NmzJcnlGMaMGaPk5GQ999xzqqio0F//+lfddNNNTj8kxcTEqGXLlrLb7Tp9+rSMMW4/V199tWXHAfjCymvJCvXVyfv375f045NrzuRJfeOP69Lb+qO28+3rcdfFZrNp7NixWrJkiY4dO6YFCxbIGKORI0fqb3/7m8fbaYiYmBglJCSovLxcpaWlLt//fKDElxj5WobrikUo1t8xMTGSpCNHjvh1PytWrHD8IOZOzXk5evSoT9v3pV/WEN6WUUkaN26c7Ha78vLy6tz28uXLtW/fPg0dOlTnnHOO03f+6kt6WydZqbi42O3yn9fDdZ1vd+U3kMeE0GZFPd8Y7Zi/eNO38LUfYrfbtWTJEr333nu6+OKLdeutt6qgoMBlfW/v9STuuT3RFMs45RpAU2fVGI6n913+GKvwNg+SdWMvAADAGeOc7jHOCYQ+JksCgAeuu+46SdKHH37o8l337t11zz33OC0rLy93GSz/+uuvtW/fPmVkZCglJcV/mQ0h3pynlJQU7d271yltUVGRdu/e7XbbcXFxTj9MXHDBBXr55Ze9yp/dbtfGjRu1YsUKtW3bVuPHj9fZZ5/tGFArKytzu15MTIzuuOMOHThwQH/961/19ttva8KECS7pRo4cqcrKSq1YscLluyeffFLnnHOOKisrvcozYDUrriWr1dTJH3zwgdPyiooKLV26VLGxsS6vNfC0vrHyuqyqqvK6/qjrfPty3HVp2bKlNm/eLEmKiorSr371Ky1YsEA2m81lH/5U8zqtmldS1CgqKtLWrVtd0nsbI1/LcF3rBWv9PWXKFN1www1uv1u0aJEk11edWc0YowMHDmj16tVuv//yyy8l/dh/8pW3/bKG8raMnn/++Zo+fbrWrFmjl156ye02T548qYkTJyopKcnlL7Yl6/uSvvZprFRaWur4C/Ma7o6ptvN96NAhbdmyxWmZL/UsUMOqet7f7Zg/edO38KUfkpCQoNTUVDVv3lzvv/++mjdvrhEjRri8Ysvbez2Je25PNLUybrfbtXnzZso1gCbNyjEcT++7rB6r8DYPVo+9AACAnzDO6R7jnEAYMAAQJiSZ3Nxcv2y7sLDQpKenm5SUFLNw4UJz/Phx88MPP5jbb7/dJCcnm++//96RNiMjwyQmJpr+/fublStXmtLSUlNQUGC6detmoqOjzbJly/ySR2OMyc7ONtnZ2X7b/tq1a40kM3z4cJfvhg8fbiSZsrIyp+VTp041kszatWudlnt7nu666y4jyfz97383JSUlZtu2bWbUqFEmNTXVJCUlueTn2muvNYmJiWb37t1m5cqVxm63m2+//dajY6kRGRlpNm3aZK655hojyTz11FPm4MGD5uTJk+a///2vOeecc4wks3jxYpd1Dx48aGJjY43NZqt1H/v37zedO3c2nTp1Mh9++KE5duyYOXz4sHnxxRdNXFycS3mu7Rz7i7/LExqXr/Gs71pyVy537txpIiIijCTz1VdfWZL/M9XUycnJySY/P98cP37cbNmyxYwcOdLYbDbz8ssvO6X3pr6x+rr0tv6o63x7e9z15S0xMdH07dvXrF+/3pSXl5v9+/ebhx9+2Egyjz/+uGfB8EJt5WLbtm2mdevWJjU11XzyySempKTEfP311+baa681HTp0MDExMU7b8TZGvpTh+tazqpxkZWWZyMhIl3PVt29fEx8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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(preprocessor, rankdir=\"LR\", show_shapes=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IURRtL_WZbht"
   },
   "source": [
    "전처리기를 테스트하려면 <a href=\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iloc.html\" class=\"external\">DataFrame.iloc</a> 접근자를 사용하여 DataFrame에서 첫 번째 예제를 조각화합니다. 그런 다음 이를 사전으로 변환하고 사전을 전처리기에 전달합니다. 결과적으로 얻어지는 것은 이진 특성, 정규화된 숫자 특성 및 원-핫 범주 특성을 순서대로 포함하는 단일 벡터입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.181620Z",
     "iopub.status.busy": "2022-12-14T20:54:06.180841Z",
     "iopub.status.idle": "2022-12-14T20:54:06.224255Z",
     "shell.execute_reply": "2022-12-14T20:54:06.223603Z"
    },
    "id": "QjBzCKsZUj0y"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(1, 33), dtype=float32, numpy=\n",
       "array([[ 1.        ,  1.        ,  0.        ,  0.93383914, -0.26008663,\n",
       "         1.0680453 ,  0.03480718,  0.74578077,  0.        ,  0.        ,\n",
       "         1.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "         0.        ,  0.        ,  1.        ,  0.        ,  0.        ,\n",
       "         0.        ,  1.        ,  0.        ,  0.        ,  0.        ,\n",
       "         1.        ,  0.        ,  0.        ,  0.        ,  1.        ,\n",
       "         0.        ,  0.        ,  0.        ]], dtype=float32)>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preprocessor(dict(df.iloc[:1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bB9C0XJkyQEk"
   },
   "source": [
    "### 모델 생성 및 훈련"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WfU_FFXMbKGM"
   },
   "source": [
    "이제 모델의 본문을 만듭니다. 이전 예와 동일한 구성을 사용합니다. 바로, 몇 개의 `Dense` rectified-linear 레이어와 분류를 위한 `Dense(1)` 출력 레이어입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.227800Z",
     "iopub.status.busy": "2022-12-14T20:54:06.227309Z",
     "iopub.status.idle": "2022-12-14T20:54:06.236576Z",
     "shell.execute_reply": "2022-12-14T20:54:06.236007Z"
    },
    "id": "75OxXTnfboKN"
   },
   "outputs": [],
   "source": [
    "body = tf.keras.Sequential([\n",
    "  tf.keras.layers.Dense(10, activation='relu'),\n",
    "  tf.keras.layers.Dense(10, activation='relu'),\n",
    "  tf.keras.layers.Dense(1)\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MpD6WNX5_zh5"
   },
   "source": [
    "이제 Keras functional API를 사용하여 두 조각을 함께 연결합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.239717Z",
     "iopub.status.busy": "2022-12-14T20:54:06.239247Z",
     "iopub.status.idle": "2022-12-14T20:54:06.243711Z",
     "shell.execute_reply": "2022-12-14T20:54:06.243151Z"
    },
    "id": "_TY_BuVMbNcB"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'age': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'age')>,\n",
       " 'sex': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'sex')>,\n",
       " 'cp': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'cp')>,\n",
       " 'trestbps': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'trestbps')>,\n",
       " 'chol': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'chol')>,\n",
       " 'fbs': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'fbs')>,\n",
       " 'restecg': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'restecg')>,\n",
       " 'thalach': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'thalach')>,\n",
       " 'exang': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'exang')>,\n",
       " 'oldpeak': <KerasTensor: shape=(None,) dtype=float32 (created by layer 'oldpeak')>,\n",
       " 'slope': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'slope')>,\n",
       " 'ca': <KerasTensor: shape=(None,) dtype=int64 (created by layer 'ca')>,\n",
       " 'thal': <KerasTensor: shape=(None,) dtype=string (created by layer 'thal')>}"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.247007Z",
     "iopub.status.busy": "2022-12-14T20:54:06.246469Z",
     "iopub.status.idle": "2022-12-14T20:54:06.333926Z",
     "shell.execute_reply": "2022-12-14T20:54:06.333288Z"
    },
    "id": "iin2kvA9bDpz"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KerasTensor: shape=(None, 33) dtype=float32 (created by layer 'model_1')>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = preprocessor(inputs)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.337378Z",
     "iopub.status.busy": "2022-12-14T20:54:06.336886Z",
     "iopub.status.idle": "2022-12-14T20:54:06.379688Z",
     "shell.execute_reply": "2022-12-14T20:54:06.379019Z"
    },
    "id": "FQd9PcPRpkP4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'sequential_3')>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = body(x)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.383212Z",
     "iopub.status.busy": "2022-12-14T20:54:06.382729Z",
     "iopub.status.idle": "2022-12-14T20:54:06.395871Z",
     "shell.execute_reply": "2022-12-14T20:54:06.395230Z"
    },
    "id": "v_KerrXabhgP"
   },
   "outputs": [],
   "source": [
    "model = tf.keras.Model(inputs, result)\n",
    "\n",
    "model.compile(optimizer='adam',\n",
    "                loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
    "                metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S1MR-XD9kC6C"
   },
   "source": [
    "이 모델은 입력 사전을 예상합니다. 데이터를 전달하는 가장 간단한 방법은 DataFrame을 dict로 변환하고 해당 dict를 `Model.fit`에 `x` 인수로 전달하는 것입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:06.399310Z",
     "iopub.status.busy": "2022-12-14T20:54:06.398893Z",
     "iopub.status.idle": "2022-12-14T20:54:11.530549Z",
     "shell.execute_reply": "2022-12-14T20:54:11.529724Z"
    },
    "id": "ybDzNUheqxJw"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 3:55 - loss: 0.7060 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 12/152 [=>............................] - ETA: 0s - loss: 0.6839 - accuracy: 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\r",
      " 23/152 [===>..........................] - ETA: 0s - loss: 0.6487 - accuracy: 0.7174"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/152 [=====>........................] - ETA: 0s - loss: 0.6341 - accuracy: 0.7857"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/152 [========>.....................] - ETA: 0s - loss: 0.6324 - accuracy: 0.7609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.6213 - accuracy: 0.7672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/152 [============>.................] - ETA: 0s - loss: 0.6110 - accuracy: 0.7714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/152 [==============>...............] - ETA: 0s - loss: 0.6080 - accuracy: 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\r",
      " 92/152 [=================>............] - ETA: 0s - loss: 0.6051 - accuracy: 0.7391"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/152 [===================>..........] - ETA: 0s - loss: 0.6071 - accuracy: 0.7282"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.5946 - accuracy: 0.7348"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.5969 - accuracy: 0.7283"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.5959 - accuracy: 0.7230"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.5859 - accuracy: 0.7252"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 2s 5ms/step - loss: 0.5852 - accuracy: 0.7261\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.4935 - accuracy: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.5104 - accuracy: 0.7308"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 0s - loss: 0.5463 - accuracy: 0.6600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 0s - loss: 0.5099 - accuracy: 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\r",
      " 49/152 [========>.....................] - ETA: 0s - loss: 0.5047 - accuracy: 0.7347"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 0s - loss: 0.5015 - accuracy: 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\r",
      " 73/152 [=============>................] - ETA: 0s - loss: 0.4833 - accuracy: 0.7740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/152 [===============>..............] - ETA: 0s - loss: 0.4743 - accuracy: 0.7824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.4604 - accuracy: 0.7865"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "108/152 [====================>.........] - ETA: 0s - loss: 0.4600 - accuracy: 0.7824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "120/152 [======================>.......] - ETA: 0s - loss: 0.4671 - accuracy: 0.7750"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "144/152 [===========================>..] - ETA: 0s - loss: 0.4622 - accuracy: 0.7639"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - 1s 4ms/step - loss: 0.4585 - accuracy: 0.7657\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1753 - accuracy: 1.0000"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/152 [==========>...................] - ETA: 0s - loss: 0.4081 - accuracy: 0.7797"
     ]
    },
    {
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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\r",
      " 71/152 [=============>................] - ETA: 0s - loss: 0.4048 - accuracy: 0.7676"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/152 [=================>............] - ETA: 0s - loss: 0.3995 - accuracy: 0.7895"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "119/152 [======================>.......] - ETA: 0s - loss: 0.3979 - accuracy: 0.7773"
     ]
    },
    {
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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\r",
      "131/152 [========================>.....] - ETA: 0s - loss: 0.3853 - accuracy: 0.7863"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.3848 - accuracy: 0.7797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 5ms/step - loss: 0.3868 - accuracy: 0.7756\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1703 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.2550 - accuracy: 0.8077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 0s - loss: 0.3369 - accuracy: 0.7800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 0s - loss: 0.3219 - accuracy: 0.7838"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      " 61/152 [===========>..................] - ETA: 0s - loss: 0.3299 - accuracy: 0.8033"
     ]
    },
    {
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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\r",
      " 73/152 [=============>................] - ETA: 0s - loss: 0.3151 - accuracy: 0.8151"
     ]
    },
    {
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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\r",
      " 84/152 [===============>..............] - ETA: 0s - loss: 0.3271 - accuracy: 0.8095"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "119/152 [======================>.......] - ETA: 0s - loss: 0.3228 - accuracy: 0.8235"
     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
      "141/152 [==========================>...] - ETA: 0s - loss: 0.3377 - accuracy: 0.8191"
     ]
    },
    {
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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\r",
      "152/152 [==============================] - ETA: 0s - loss: 0.3471 - accuracy: 0.8119"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 5ms/step - loss: 0.3471 - accuracy: 0.8119\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.3056 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.3067 - accuracy: 0.8462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 0s - loss: 0.3621 - accuracy: 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\r",
      " 36/152 [======>.......................] - ETA: 0s - loss: 0.3276 - accuracy: 0.8194"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 47/152 [========>.....................] - ETA: 0s - loss: 0.3058 - accuracy: 0.8298"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 58/152 [==========>...................] - ETA: 0s - loss: 0.2834 - accuracy: 0.8448"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/152 [============>.................] - ETA: 0s - loss: 0.2994 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/152 [==============>...............] - ETA: 0s - loss: 0.2850 - accuracy: 0.8375"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/152 [================>.............] - ETA: 0s - loss: 0.2828 - accuracy: 0.8462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "102/152 [===================>..........] - ETA: 0s - loss: 0.2976 - accuracy: 0.8382"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "114/152 [=====================>........] - ETA: 0s - loss: 0.3012 - accuracy: 0.8289"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "126/152 [=======================>......] - ETA: 0s - loss: 0.3005 - accuracy: 0.8294"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "138/152 [==========================>...] - ETA: 0s - loss: 0.3108 - accuracy: 0.8261"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "150/152 [============================>.] - ETA: 0s - loss: 0.3274 - accuracy: 0.8167"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 5ms/step - loss: 0.3270 - accuracy: 0.8185\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(dict(df), target, epochs=5, batch_size=BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dacoEIB_BSsL"
   },
   "source": [
    "`tf.data`를 사용해도 됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:11.534485Z",
     "iopub.status.busy": "2022-12-14T20:54:11.533906Z",
     "iopub.status.idle": "2022-12-14T20:54:11.558779Z",
     "shell.execute_reply": "2022-12-14T20:54:11.558008Z"
    },
    "id": "rYadV3wwE4G3"
   },
   "outputs": [],
   "source": [
    "ds = tf.data.Dataset.from_tensor_slices((\n",
    "    dict(df),\n",
    "    target\n",
    "))\n",
    "\n",
    "ds = ds.batch(BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:11.562691Z",
     "iopub.status.busy": "2022-12-14T20:54:11.562097Z",
     "iopub.status.idle": "2022-12-14T20:54:11.581460Z",
     "shell.execute_reply": "2022-12-14T20:54:11.580652Z"
    },
    "id": "2YIpp2r0bv-6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'age': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([63, 67])>,\n",
      " 'ca': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([0, 3])>,\n",
      " 'chol': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([233, 286])>,\n",
      " 'cp': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([1, 4])>,\n",
      " 'exang': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([0, 1])>,\n",
      " 'fbs': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([1, 0])>,\n",
      " 'oldpeak': <tf.Tensor: shape=(2,), dtype=float64, numpy=array([2.3, 1.5])>,\n",
      " 'restecg': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([2, 2])>,\n",
      " 'sex': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([1, 1])>,\n",
      " 'slope': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([3, 2])>,\n",
      " 'thal': <tf.Tensor: shape=(2,), dtype=string, numpy=array([b'fixed', b'normal'], dtype=object)>,\n",
      " 'thalach': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([150, 108])>,\n",
      " 'trestbps': <tf.Tensor: shape=(2,), dtype=int64, numpy=array([145, 160])>}\n",
      "\n",
      "tf.Tensor([0 1], shape=(2,), dtype=int64)\n"
     ]
    }
   ],
   "source": [
    "import pprint\n",
    "\n",
    "for x, y in ds.take(1):\n",
    "  pprint.pprint(x)\n",
    "  print()\n",
    "  print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T20:54:11.585367Z",
     "iopub.status.busy": "2022-12-14T20:54:11.584843Z",
     "iopub.status.idle": "2022-12-14T20:54:15.484760Z",
     "shell.execute_reply": "2022-12-14T20:54:15.484022Z"
    },
    "id": "NMT-AevGFmdu"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 1:04 - loss: 0.1742 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.2546 - accuracy: 0.8846  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 0s - loss: 0.3122 - accuracy: 0.8400"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/152 [======>.......................] - ETA: 0s - loss: 0.2727 - accuracy: 0.8611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/152 [========>.....................] - ETA: 0s - loss: 0.2431 - accuracy: 0.8854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/152 [==========>...................] - ETA: 0s - loss: 0.2692 - accuracy: 0.8833"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/152 [=============>................] - ETA: 0s - loss: 0.2886 - accuracy: 0.8611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/152 [===============>..............] - ETA: 0s - loss: 0.2789 - accuracy: 0.8631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.2780 - accuracy: 0.8646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "108/152 [====================>.........] - ETA: 0s - loss: 0.2995 - accuracy: 0.8426"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "120/152 [======================>.......] - ETA: 0s - loss: 0.2971 - accuracy: 0.8500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/152 [========================>.....] - ETA: 0s - loss: 0.2917 - accuracy: 0.8588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.3013 - accuracy: 0.8601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 4ms/step - loss: 0.3107 - accuracy: 0.8548\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1596 - accuracy: 1.0000"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/152 [==========>...................] - ETA: 0s - loss: 0.2530 - accuracy: 0.8833"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 72/152 [=============>................] - ETA: 0s - loss: 0.2726 - accuracy: 0.8611"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/152 [===============>..............] - ETA: 0s - loss: 0.2638 - accuracy: 0.8631"
     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 96/152 [=================>............] - ETA: 0s - loss: 0.2641 - accuracy: 0.8646"
     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "120/152 [======================>.......] - ETA: 0s - loss: 0.2833 - accuracy: 0.8500"
     ]
    },
    {
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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\r",
      "132/152 [=========================>....] - ETA: 0s - loss: 0.2760 - accuracy: 0.8598"
     ]
    },
    {
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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\r",
      "143/152 [===========================>..] - ETA: 0s - loss: 0.2883 - accuracy: 0.8601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 4ms/step - loss: 0.2972 - accuracy: 0.8548\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1502 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.2320 - accuracy: 0.8846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/152 [===>..........................] - ETA: 0s - loss: 0.2873 - accuracy: 0.8542"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/152 [=====>........................] - ETA: 0s - loss: 0.2538 - accuracy: 0.8714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/152 [========>.....................] - ETA: 0s - loss: 0.2229 - accuracy: 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\r",
      " 57/152 [==========>...................] - ETA: 0s - loss: 0.2475 - accuracy: 0.9035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 69/152 [============>.................] - ETA: 0s - loss: 0.2668 - accuracy: 0.8913"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 80/152 [==============>...............] - ETA: 0s - loss: 0.2562 - accuracy: 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\r",
      " 91/152 [================>.............] - ETA: 0s - loss: 0.2570 - accuracy: 0.8846"
     ]
    },
    {
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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\r",
      "103/152 [===================>..........] - ETA: 0s - loss: 0.2740 - accuracy: 0.8689"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/152 [=====================>........] - ETA: 0s - loss: 0.2714 - accuracy: 0.8652"
     ]
    },
    {
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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\r",
      "127/152 [========================>.....] - ETA: 0s - loss: 0.2702 - accuracy: 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\r",
      "139/152 [==========================>...] - ETA: 0s - loss: 0.2833 - accuracy: 0.8669"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/152 [============================>.] - ETA: 0s - loss: 0.2878 - accuracy: 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\r",
      "152/152 [==============================] - 1s 5ms/step - loss: 0.2870 - accuracy: 0.8647\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1446 - accuracy: 1.0000"
     ]
    },
    {
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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\r",
      " 12/152 [=>............................] - ETA: 0s - loss: 0.2339 - accuracy: 0.8333"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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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\r",
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     ]
    },
    {
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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\r",
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    },
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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\r",
      " 60/152 [==========>...................] - ETA: 0s - loss: 0.2367 - accuracy: 0.9000"
     ]
    },
    {
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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\r",
      " 72/152 [=============>................] - ETA: 0s - loss: 0.2554 - accuracy: 0.8819"
     ]
    },
    {
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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\r",
      " 83/152 [===============>..............] - ETA: 0s - loss: 0.2495 - accuracy: 0.8795"
     ]
    },
    {
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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\r",
      " 95/152 [=================>............] - ETA: 0s - loss: 0.2431 - accuracy: 0.8842"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "107/152 [====================>.........] - ETA: 0s - loss: 0.2706 - accuracy: 0.8551"
     ]
    },
    {
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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\r",
      "118/152 [======================>.......] - ETA: 0s - loss: 0.2645 - accuracy: 0.8602"
     ]
    },
    {
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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\r",
      "130/152 [========================>.....] - ETA: 0s - loss: 0.2600 - accuracy: 0.8654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "142/152 [===========================>..] - ETA: 0s - loss: 0.2725 - accuracy: 0.8662"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 5ms/step - loss: 0.2784 - accuracy: 0.8614\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/152 [..............................] - ETA: 0s - loss: 0.1432 - accuracy: 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\r",
      " 13/152 [=>............................] - ETA: 0s - loss: 0.2176 - accuracy: 0.8462"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/152 [===>..........................] - ETA: 0s - loss: 0.2627 - accuracy: 0.8600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/152 [======>.......................] - ETA: 0s - loss: 0.2332 - accuracy: 0.8784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/152 [========>.....................] - ETA: 0s - loss: 0.2036 - accuracy: 0.9082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 61/152 [===========>..................] - ETA: 0s - loss: 0.2279 - accuracy: 0.9098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/152 [=============>................] - ETA: 0s - loss: 0.2458 - accuracy: 0.8904"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/152 [===============>..............] - ETA: 0s - loss: 0.2372 - accuracy: 0.8882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 97/152 [==================>...........] - ETA: 0s - loss: 0.2502 - accuracy: 0.8763"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/152 [====================>.........] - ETA: 0s - loss: 0.2654 - accuracy: 0.8578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/152 [======================>.......] - ETA: 0s - loss: 0.2555 - accuracy: 0.8636"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/152 [=========================>....] - ETA: 0s - loss: 0.2570 - accuracy: 0.8684"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "144/152 [===========================>..] - ETA: 0s - loss: 0.2615 - accuracy: 0.8646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "152/152 [==============================] - 1s 4ms/step - loss: 0.2704 - accuracy: 0.8581\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(ds, epochs=5)"
   ]
  }
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