{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MhoQ0WE77laV"
   },
   "source": [
    "##### Copyright 2018 The TensorFlow Authors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:20.884761Z",
     "iopub.status.busy": "2022-12-15T00:31:20.884525Z",
     "iopub.status.idle": "2022-12-15T00:31:20.888736Z",
     "shell.execute_reply": "2022-12-15T00:31:20.888049Z"
    },
    "id": "_ckMIh7O7s6D"
   },
   "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": "code",
   "execution_count": 2,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:20.891926Z",
     "iopub.status.busy": "2022-12-15T00:31:20.891421Z",
     "iopub.status.idle": "2022-12-15T00:31:20.894876Z",
     "shell.execute_reply": "2022-12-15T00:31:20.894217Z"
    },
    "id": "vasWnqRgy1H4"
   },
   "outputs": [],
   "source": [
    "#@title MIT License\n",
    "#\n",
    "# Copyright (c) 2017 François Chollet\n",
    "#\n",
    "# Permission is hereby granted, free of charge, to any person obtaining a\n",
    "# copy of this software and associated documentation files (the \"Software\"),\n",
    "# to deal in the Software without restriction, including without limitation\n",
    "# the rights to use, copy, modify, merge, publish, distribute, sublicense,\n",
    "# and/or sell copies of the Software, and to permit persons to whom the\n",
    "# Software is furnished to do so, subject to the following conditions:\n",
    "#\n",
    "# The above copyright notice and this permission notice shall be included in\n",
    "# all copies or substantial portions of the Software.\n",
    "#\n",
    "# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n",
    "# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n",
    "# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\n",
    "# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n",
    "# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n",
    "# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\n",
    "# DEALINGS IN THE SOFTWARE."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jYysdyb-CaWM"
   },
   "source": [
    "# はじめてのニューラルネットワーク：分類問題の初歩"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S5Uhzt6vVIB2"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td><a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/keras/classification\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\">TensorFlow.org で表示</a></td>\n",
    "  <td>     <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs-l10n/blob/master/site/ja/tutorials/keras/classification.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\">Run in Google Colab</a>   </td>\n",
    "  <td>     <a target=\"_blank\" href=\"https://github.com/tensorflow/docs-l10n/blob/master/site/ja/tutorials/keras/classification.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\">GitHub でソースを表示</a> </td>\n",
    "  <td>     <a href=\"https://storage.googleapis.com/tensorflow_docs/docs-l10n/site/ja/tutorials/keras/classification.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\">ノートブックをダウンロード</a> </td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FbVhjPpzn6BM"
   },
   "source": [
    "このガイドでは、スニーカーやシャツなど、身に着けるものの画像を分類するニューラルネットワークのモデルをトレーニングします。すべての詳細を理解できなくても問題ありません。ここでは、完全な TensorFlow プログラムについて概説し、細かいところはその過程において見ていきます。\n",
    "\n",
    "このガイドでは、TensorFlowのモデルを構築し訓練するためのハイレベルのAPIである [tf.keras](https://www.tensorflow.org/guide/keras)を使用します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:20.898506Z",
     "iopub.status.busy": "2022-12-15T00:31:20.897915Z",
     "iopub.status.idle": "2022-12-15T00:31:23.302426Z",
     "shell.execute_reply": "2022-12-15T00:31:23.301647Z"
    },
    "id": "dzLKpmZICaWN"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-15 00:31:21.895161: 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",
      "2022-12-15 00:31:21.895268: 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",
      "2022-12-15 00:31:21.895278: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.11.0\n"
     ]
    }
   ],
   "source": [
    "# TensorFlow and tf.keras\n",
    "import tensorflow as tf\n",
    "\n",
    "# Helper libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "print(tf.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yR0EdgrLCaWR"
   },
   "source": [
    "## Fashion MNIST データセットをインポートする"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DLdCchMdCaWQ"
   },
   "source": [
    "このガイドでは、[Fashion MNIST](https://github.com/zalandoresearch/fashion-mnist) データセットを使用します。このデータセットには、10 カテゴリの 70,000 のグレースケール画像が含まれています。次のように、画像は低解像度（28 x 28 ピクセル）で個々の衣料品を示しています。\n",
    "\n",
    "<table>\n",
    "  <tr><td>     <img src=\"https://tensorflow.org/images/fashion-mnist-sprite.png\" alt=\"Fashion MNIST sprite\" width=\"600\">   </td></tr>\n",
    "  <tr><td align=\"center\">     <b>図 1.</b> <a href=\"https://github.com/zalandoresearch/fashion-mnist\">Fashion-MNIST サンプル</a> (作成者：Zalando、MIT ライセンス)<br> </td></tr>\n",
    "</table>\n",
    "\n",
    "Fashion MNISTは、画像処理のための機械学習での\"Hello, World\"としてしばしば登場する[MNIST](http://yann.lecun.com/exdb/mnist/) データセットの代替として開発されたものです。MNISTデータセットは手書きの数字（0, 1, 2 など）から構成されており、そのフォーマットはこれから使うFashion MNISTと全く同じです。\n",
    "\n",
    "Fashion MNIST を使うのは、目先を変える意味もありますが、普通の MNIST よりも少しだけ手応えがあるからでもあります。どちらのデータセットも比較的小さく、アルゴリズムが期待したとおりに機能するかどうかを確認するために使われます。プログラムのテストやデバッグのためには、よい出発点になります。\n",
    "\n",
    "ここでは、60,000 枚の画像を使用してネットワークをトレーニングし、10,000 枚の画像を使用して、ネットワークが画像の分類をどの程度正確に学習したかを評価します。Tensor Flow から直接 Fashion MNIST にアクセスできます。Tensor Flow から直接 [Fashion MNIST データをインポートして読み込みます](https://www.tensorflow.org/api_docs/python/tf/keras/datasets/fashion_mnist/load_data)。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.306516Z",
     "iopub.status.busy": "2022-12-15T00:31:23.305782Z",
     "iopub.status.idle": "2022-12-15T00:31:23.709338Z",
     "shell.execute_reply": "2022-12-15T00:31:23.708550Z"
    },
    "id": "7MqDQO0KCaWS"
   },
   "outputs": [],
   "source": [
    "fashion_mnist = tf.keras.datasets.fashion_mnist\n",
    "\n",
    "(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "t9FDsUlxCaWW"
   },
   "source": [
    "読み込んだデータセットは、NumPy 配列になります。\n",
    "\n",
    "- `train_images` と `train_labels` の 2 つの配列は、モデルのトレーニングに使用される*トレーニング用データセット*です。\n",
    "- モデルは、*テストセット*、`test_images`および`test_labels`  配列に対してテストされます。\n",
    "\n",
    "画像は 28×28 の NumPy 配列から構成されています。それぞれのピクセルの値は 0 から 255 の間です。*ラベル*は、0 から 9 までの整数の配列です。それぞれの数字が下表のように、衣料品の*クラス*に対応しています。\n",
    "\n",
    "<table>\n",
    "  <tr>\n",
    "    <th>Label</th>\n",
    "    <th>Class</th>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>0</td>\n",
    "    <td>T-shirt/top</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>1</td>\n",
    "    <td>Trouser</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>2</td>\n",
    "    <td>Pullover</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>3</td>\n",
    "    <td>Dress</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>4</td>\n",
    "    <td>Coat</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>5</td>\n",
    "    <td>Sandal</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>6</td>\n",
    "    <td>Shirt</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>7</td>\n",
    "    <td>Sneaker</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>8</td>\n",
    "    <td>Bag</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>9</td>\n",
    "    <td>Ankle boot</td>\n",
    "  </tr>\n",
    "</table>\n",
    "\n",
    "画像はそれぞれ単一のラベルに分類されます。データセットには上記の**クラス名**が含まれていないため、後ほど画像を出力するときのために、クラス名を保存しておきます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.713321Z",
     "iopub.status.busy": "2022-12-15T00:31:23.713085Z",
     "iopub.status.idle": "2022-12-15T00:31:23.716421Z",
     "shell.execute_reply": "2022-12-15T00:31:23.715798Z"
    },
    "id": "IjnLH5S2CaWx"
   },
   "outputs": [],
   "source": [
    "class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',\n",
    "               'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Brm0b_KACaWX"
   },
   "source": [
    "## データの観察\n",
    "\n",
    "モデルのトレーニングを行う前に、データセットの形式を見てみましょう。下記のように、トレーニング用データセットには 28 × 28 ピクセルの画像が 60,000 含まれています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.719845Z",
     "iopub.status.busy": "2022-12-15T00:31:23.719239Z",
     "iopub.status.idle": "2022-12-15T00:31:23.725652Z",
     "shell.execute_reply": "2022-12-15T00:31:23.725031Z"
    },
    "id": "zW5k_xz1CaWX"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 28, 28)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cIAcvQqMCaWf"
   },
   "source": [
    "同様に、トレーニング用データセットには 60,000 のラベルが含まれています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.729293Z",
     "iopub.status.busy": "2022-12-15T00:31:23.728671Z",
     "iopub.status.idle": "2022-12-15T00:31:23.732714Z",
     "shell.execute_reply": "2022-12-15T00:31:23.732106Z"
    },
    "id": "TRFYHB2mCaWb"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YSlYxFuRCaWk"
   },
   "source": [
    "ラベルはそれぞれ、0 から 9 までの間の整数です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.735904Z",
     "iopub.status.busy": "2022-12-15T00:31:23.735329Z",
     "iopub.status.idle": "2022-12-15T00:31:23.739612Z",
     "shell.execute_reply": "2022-12-15T00:31:23.738985Z"
    },
    "id": "XKnCTHz4CaWg"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([9, 0, 0, ..., 3, 0, 5], dtype=uint8)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TMPI88iZpO2T"
   },
   "source": [
    "テスト用データセットには、10,000 の画像が含まれます。画像は 28 × 28 ピクセルで構成されています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.742784Z",
     "iopub.status.busy": "2022-12-15T00:31:23.742295Z",
     "iopub.status.idle": "2022-12-15T00:31:23.746129Z",
     "shell.execute_reply": "2022-12-15T00:31:23.745546Z"
    },
    "id": "2KFnYlcwCaWl"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 28, 28)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_images.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rd0A0Iu0CaWq"
   },
   "source": [
    "テスト用データセットには 10,000 のラベルが含まれます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.749449Z",
     "iopub.status.busy": "2022-12-15T00:31:23.748835Z",
     "iopub.status.idle": "2022-12-15T00:31:23.752939Z",
     "shell.execute_reply": "2022-12-15T00:31:23.752284Z"
    },
    "id": "iJmPr5-ACaWn"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(test_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ES6uQoLKCaWr"
   },
   "source": [
    "## データの前処理\n",
    "\n",
    "ネットワークをトレーニングする前に、データを前処理する必要があります。最初の画像を調べてみればわかるように、ピクセルの値は 0 から 255 の間の数値です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.756582Z",
     "iopub.status.busy": "2022-12-15T00:31:23.755966Z",
     "iopub.status.idle": "2022-12-15T00:31:23.927984Z",
     "shell.execute_reply": "2022-12-15T00:31:23.927298Z"
    },
    "id": "m4VEw8Ud9Quh"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.imshow(train_images[0])\n",
    "plt.colorbar()\n",
    "plt.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Wz7l27Lz9S1P"
   },
   "source": [
    "これらの値をニューラルネットワークモデルに供給する前に、0 から 1 の範囲にスケーリングします。これを行うには、値を 255 で割ります。*トレーニングセット*と*テストセット*を同じ方法で前処理することが重要です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:23.931859Z",
     "iopub.status.busy": "2022-12-15T00:31:23.931579Z",
     "iopub.status.idle": "2022-12-15T00:31:24.113761Z",
     "shell.execute_reply": "2022-12-15T00:31:24.112828Z"
    },
    "id": "bW5WzIPlCaWv"
   },
   "outputs": [],
   "source": [
    "train_images = train_images / 255.0\n",
    "\n",
    "test_images = test_images / 255.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ee638AlnCaWz"
   },
   "source": [
    "**訓練用データセット**の最初の25枚の画像を、クラス名付きで表示してみましょう。ネットワークを構築・訓練する前に、データが正しいフォーマットになっていることを確認します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:24.118559Z",
     "iopub.status.busy": "2022-12-15T00:31:24.117840Z",
     "iopub.status.idle": "2022-12-15T00:31:24.853021Z",
     "shell.execute_reply": "2022-12-15T00:31:24.852239Z"
    },
    "id": "oZTImqg_CaW1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "for i in range(25):\n",
    "    plt.subplot(5,5,i+1)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    plt.grid(False)\n",
    "    plt.imshow(train_images[i], cmap=plt.cm.binary)\n",
    "    plt.xlabel(class_names[train_labels[i]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "59veuiEZCaW4"
   },
   "source": [
    "## モデルの構築\n",
    "\n",
    "ニューラルネットワークを構築するには、まずモデルのレイヤーを定義し、その後モデルをコンパイルします。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Gxg1XGm0eOBy"
   },
   "source": [
    "### レイヤーの設定\n",
    "\n",
    "ニューラルネットワークの基本的な構成要素は、[*レイヤー*](https://www.tensorflow.org/api_docs/python/tf/keras/layers)です。レイヤーは、レイヤーに入力されたデータから表現を抽出します。 これらの表現は解決しようとする問題に有用であることが望まれます。\n",
    "\n",
    "ディープラーニングモデルのほとんどは、単純なレイヤーの積み重ねで構成されています。`tf.keras.layers.Dense` のようなレイヤーのほとんどには、トレーニング中に学習されるパラメータが存在します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:24.857344Z",
     "iopub.status.busy": "2022-12-15T00:31:24.856789Z",
     "iopub.status.idle": "2022-12-15T00:31:28.605819Z",
     "shell.execute_reply": "2022-12-15T00:31:28.604959Z"
    },
    "id": "9ODch-OFCaW4"
   },
   "outputs": [],
   "source": [
    "model = tf.keras.Sequential([\n",
    "    tf.keras.layers.Flatten(input_shape=(28, 28)),\n",
    "    tf.keras.layers.Dense(128, activation='relu'),\n",
    "    tf.keras.layers.Dense(10)\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gut8A_7rCaW6"
   },
   "source": [
    "このネットワークの最初のレイヤーは、`tf.keras.layers.Flatten` です。このレイヤーは、画像を（28 × 28 ピクセルの）2 次元配列から、28×28＝784 ピクセルの、1 次元配列に変換します。このレイヤーが、画像の中に積まれているピクセルの行を取り崩し、横に並べると考えてください。このレイヤーには学習すべきパラメータはなく、ただデータのフォーマット変換を行うだけです。\n",
    "\n",
    "ピクセルが１次元化されたあと、ネットワークは 2 つの `tf.keras.layers.Dense` レイヤーとなります。これらのレイヤーは、密結合あるいは全結合されたニューロンのレイヤーとなります。最初の `Dense` レイヤーには、128 個のノード（あるはニューロン）があります。最後のレイヤーでもある 2 番めのレイヤーは、長さが 10 のロジット配列を返します。それぞれのノードは、今見ている画像が 10 個のクラスのひとつひとつに属する確率を出力します。\n",
    "\n",
    "### モデルのコンパイル\n",
    "\n",
    "モデルのトレーニングの準備が整う前に、さらにいくつかの設定が必要です。これらは、モデルの[*コンパイル*](https://www.tensorflow.org/api_docs/python/tf/keras/Model#compile)ステップ中に追加されます。\n",
    "\n",
    "- [*損失関数*](https://www.tensorflow.org/api_docs/python/tf/keras/losses) —これは、トレーニング中のモデルの正解率を測定します。この関数を最小化して、モデルを正しい方向に「操縦」する必要があります。\n",
    "- [*オプティマイザ*](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers) —これは、モデルが表示するデータとその損失関数に基づいてモデルが更新される方法です。\n",
    "- [*指標*](https://www.tensorflow.org/api_docs/python/tf/keras/metrics) —トレーニングとテストの手順を監視するために使用されます。次の例では、正しく分類された画像の率である正解率を使用しています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:28.610463Z",
     "iopub.status.busy": "2022-12-15T00:31:28.609889Z",
     "iopub.status.idle": "2022-12-15T00:31:28.624806Z",
     "shell.execute_reply": "2022-12-15T00:31:28.624109Z"
    },
    "id": "Lhan11blCaW7"
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer='adam',\n",
    "              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qKF6uW-BCaW-"
   },
   "source": [
    "## モデルの訓練\n",
    "\n",
    "ニューラルネットワークモデルのトレーニングには、次の手順が必要です。\n",
    "\n",
    "1. モデルトレーニング用データを投入します。この例では、トレーニングデータは `train_images` および <br>`train_labels` 配列にあります。\n",
    "2. モデルは、画像とラベルの対応関係を学習します。\n",
    "3. モデルにテスト用データセットの予測（分類）を行わせます。この例では `test_images` 配列です。その後、予測結果と `test_labels` 配列を照合します。\n",
    "4. 予測が `test_labels` 配列のラベルと一致することを確認します。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z4P4zIV7E28Z"
   },
   "source": [
    "### モデルに投入する\n",
    "\n",
    "トレーニングを開始するには、[`model.fit`](https://www.tensorflow.org/api_docs/python/tf/keras/Model#fit) メソッドを呼び出します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:31:28.629046Z",
     "iopub.status.busy": "2022-12-15T00:31:28.628450Z",
     "iopub.status.idle": "2022-12-15T00:32:10.431635Z",
     "shell.execute_reply": "2022-12-15T00:32:10.430894Z"
    },
    "id": "xvwvpA64CaW_"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 42:05 - loss: 2.6907 - accuracy: 0.0000e+00"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  24/1875 [..............................] - ETA: 4s - loss: 1.5299 - accuracy: 0.5182       "
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  48/1875 [..............................] - ETA: 3s - loss: 1.1985 - accuracy: 0.6133"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  72/1875 [>.............................] - ETA: 3s - loss: 1.0636 - accuracy: 0.6562"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  95/1875 [>.............................] - ETA: 3s - loss: 0.9703 - accuracy: 0.6816"
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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\r",
      " 118/1875 [>.............................] - ETA: 3s - loss: 0.9167 - accuracy: 0.6965"
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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\b\b\r",
      " 166/1875 [=>............................] - ETA: 3s - loss: 0.8269 - accuracy: 0.7246"
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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\r",
      " 189/1875 [==>...........................] - ETA: 3s - loss: 0.8015 - accuracy: 0.7321"
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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\r",
      " 212/1875 [==>...........................] - ETA: 3s - loss: 0.7763 - accuracy: 0.7406"
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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\r",
      " 236/1875 [==>...........................] - ETA: 3s - loss: 0.7554 - accuracy: 0.7455"
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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\b\b\r",
      " 260/1875 [===>..........................] - ETA: 3s - loss: 0.7298 - accuracy: 0.7530"
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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\r",
      " 284/1875 [===>..........................] - ETA: 3s - loss: 0.7159 - accuracy: 0.7572"
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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\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\b\b\r",
      " 332/1875 [====>.........................] - ETA: 3s - loss: 0.6945 - accuracy: 0.7640"
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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\b\b\r",
      " 355/1875 [====>.........................] - ETA: 3s - loss: 0.6852 - accuracy: 0.7669"
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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\r",
      " 378/1875 [=====>........................] - ETA: 3s - loss: 0.6754 - accuracy: 0.7698"
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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\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\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\b\b\r",
      " 449/1875 [======>.......................] - ETA: 3s - loss: 0.6549 - accuracy: 0.7771"
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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\r",
      " 473/1875 [======>.......................] - ETA: 3s - loss: 0.6478 - accuracy: 0.7789"
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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\b\b\r",
      " 497/1875 [======>.......................] - ETA: 2s - loss: 0.6411 - accuracy: 0.7801"
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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\b\b\r",
      " 521/1875 [=======>......................] - ETA: 2s - loss: 0.6370 - accuracy: 0.7817"
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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\b\b\r",
      " 545/1875 [=======>......................] - ETA: 2s - loss: 0.6311 - 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\b\b\r",
      " 569/1875 [========>.....................] - ETA: 2s - loss: 0.6244 - accuracy: 0.7859"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 593/1875 [========>.....................] - ETA: 2s - loss: 0.6159 - accuracy: 0.7887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 616/1875 [========>.....................] - ETA: 2s - loss: 0.6121 - 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\b\b\r",
      " 639/1875 [=========>....................] - ETA: 2s - loss: 0.6065 - accuracy: 0.7912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 663/1875 [=========>....................] - ETA: 2s - loss: 0.6036 - 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\b\b\r",
      " 686/1875 [=========>....................] - ETA: 2s - loss: 0.5975 - accuracy: 0.7931"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 710/1875 [==========>...................] - ETA: 2s - loss: 0.5919 - accuracy: 0.7942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 734/1875 [==========>...................] - ETA: 2s - loss: 0.5908 - accuracy: 0.7944"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 757/1875 [===========>..................] - ETA: 2s - loss: 0.5856 - accuracy: 0.7962"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 781/1875 [===========>..................] - ETA: 2s - loss: 0.5808 - 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\b\b\r",
      " 805/1875 [===========>..................] - ETA: 2s - loss: 0.5776 - accuracy: 0.7990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 829/1875 [============>.................] - ETA: 2s - loss: 0.5733 - accuracy: 0.8002"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 853/1875 [============>.................] - ETA: 2s - loss: 0.5700 - accuracy: 0.8016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 876/1875 [=============>................] - ETA: 2s - loss: 0.5681 - accuracy: 0.8019"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 900/1875 [=============>................] - ETA: 2s - loss: 0.5686 - accuracy: 0.8018"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 924/1875 [=============>................] - ETA: 2s - loss: 0.5655 - accuracy: 0.8031"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 947/1875 [==============>...............] - ETA: 2s - loss: 0.5644 - accuracy: 0.8033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 971/1875 [==============>...............] - ETA: 1s - loss: 0.5627 - accuracy: 0.8040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 995/1875 [==============>...............] - ETA: 1s - loss: 0.5604 - accuracy: 0.8045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1018/1875 [===============>..............] - ETA: 1s - loss: 0.5571 - accuracy: 0.8058"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1041/1875 [===============>..............] - ETA: 1s - loss: 0.5548 - accuracy: 0.8067"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1064/1875 [================>.............] - ETA: 1s - loss: 0.5532 - accuracy: 0.8074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1088/1875 [================>.............] - ETA: 1s - loss: 0.5506 - accuracy: 0.8081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1112/1875 [================>.............] - ETA: 1s - loss: 0.5471 - accuracy: 0.8092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1135/1875 [=================>............] - ETA: 1s - loss: 0.5453 - accuracy: 0.8098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1158/1875 [=================>............] - ETA: 1s - loss: 0.5439 - accuracy: 0.8103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1181/1875 [=================>............] - ETA: 1s - loss: 0.5421 - accuracy: 0.8109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1204/1875 [==================>...........] - ETA: 1s - loss: 0.5406 - accuracy: 0.8115"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1227/1875 [==================>...........] - ETA: 1s - loss: 0.5388 - accuracy: 0.8120"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1249/1875 [==================>...........] - ETA: 1s - loss: 0.5364 - accuracy: 0.8129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1272/1875 [===================>..........] - ETA: 1s - loss: 0.5343 - accuracy: 0.8137"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1295/1875 [===================>..........] - ETA: 1s - loss: 0.5327 - accuracy: 0.8143"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1318/1875 [====================>.........] - ETA: 1s - loss: 0.5308 - accuracy: 0.8151"
     ]
    },
    {
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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\r",
      "1341/1875 [====================>.........] - ETA: 1s - loss: 0.5297 - accuracy: 0.8156"
     ]
    },
    {
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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\r",
      "1364/1875 [====================>.........] - ETA: 1s - loss: 0.5280 - accuracy: 0.8162"
     ]
    },
    {
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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\r",
      "1386/1875 [=====================>........] - ETA: 1s - loss: 0.5266 - accuracy: 0.8168"
     ]
    },
    {
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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\r",
      "1409/1875 [=====================>........] - ETA: 1s - loss: 0.5250 - accuracy: 0.8174"
     ]
    },
    {
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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\r",
      "1433/1875 [=====================>........] - ETA: 0s - loss: 0.5244 - accuracy: 0.8178"
     ]
    },
    {
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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\r",
      "1456/1875 [======================>.......] - ETA: 0s - loss: 0.5231 - accuracy: 0.8181"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1479/1875 [======================>.......] - ETA: 0s - loss: 0.5219 - accuracy: 0.8183"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1501/1875 [=======================>......] - ETA: 0s - loss: 0.5211 - accuracy: 0.8186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1524/1875 [=======================>......] - ETA: 0s - loss: 0.5195 - accuracy: 0.8192"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1547/1875 [=======================>......] - ETA: 0s - loss: 0.5184 - accuracy: 0.8196"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1569/1875 [========================>.....] - ETA: 0s - loss: 0.5174 - accuracy: 0.8199"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1591/1875 [========================>.....] - ETA: 0s - loss: 0.5159 - accuracy: 0.8203"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1613/1875 [========================>.....] - ETA: 0s - loss: 0.5145 - accuracy: 0.8206"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1637/1875 [=========================>....] - ETA: 0s - loss: 0.5132 - accuracy: 0.8210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1661/1875 [=========================>....] - ETA: 0s - loss: 0.5122 - accuracy: 0.8213"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1685/1875 [=========================>....] - ETA: 0s - loss: 0.5112 - accuracy: 0.8217"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1708/1875 [==========================>...] - ETA: 0s - loss: 0.5101 - accuracy: 0.8219"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1731/1875 [==========================>...] - ETA: 0s - loss: 0.5089 - 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\b\b\r",
      "1755/1875 [===========================>..] - ETA: 0s - loss: 0.5083 - accuracy: 0.8223"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1778/1875 [===========================>..] - ETA: 0s - loss: 0.5071 - accuracy: 0.8226"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1801/1875 [===========================>..] - ETA: 0s - loss: 0.5056 - accuracy: 0.8231"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1825/1875 [============================>.] - ETA: 0s - loss: 0.5046 - accuracy: 0.8234"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1849/1875 [============================>.] - ETA: 0s - loss: 0.5032 - accuracy: 0.8238"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1873/1875 [============================>.] - ETA: 0s - loss: 0.5022 - accuracy: 0.8240"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 5s 2ms/step - loss: 0.5022 - accuracy: 0.8239\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.5548 - 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\b\b\r",
      "  25/1875 [..............................] - ETA: 3s - loss: 0.3805 - 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\b\b\r",
      "  48/1875 [..............................] - ETA: 3s - loss: 0.3969 - accuracy: 0.8685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  71/1875 [>.............................] - ETA: 3s - loss: 0.3827 - accuracy: 0.8706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  94/1875 [>.............................] - ETA: 3s - loss: 0.3901 - accuracy: 0.8707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 116/1875 [>.............................] - ETA: 3s - loss: 0.3863 - accuracy: 0.8680"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 139/1875 [=>............................] - ETA: 3s - loss: 0.3760 - accuracy: 0.8716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 162/1875 [=>............................] - ETA: 3s - loss: 0.3714 - accuracy: 0.8721"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 186/1875 [=>............................] - ETA: 3s - loss: 0.3760 - accuracy: 0.8690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 209/1875 [==>...........................] - ETA: 3s - loss: 0.3787 - accuracy: 0.8663"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 233/1875 [==>...........................] - ETA: 3s - loss: 0.3764 - accuracy: 0.8663"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 257/1875 [===>..........................] - ETA: 3s - loss: 0.3820 - accuracy: 0.8628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 280/1875 [===>..........................] - ETA: 3s - loss: 0.3806 - 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\b\b\r",
      " 304/1875 [===>..........................] - ETA: 3s - loss: 0.3874 - accuracy: 0.8629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 328/1875 [====>.........................] - ETA: 3s - loss: 0.3876 - accuracy: 0.8627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 352/1875 [====>.........................] - ETA: 3s - loss: 0.3859 - 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\b\b\r",
      " 375/1875 [=====>........................] - ETA: 3s - loss: 0.3879 - accuracy: 0.8626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 398/1875 [=====>........................] - ETA: 3s - loss: 0.3862 - accuracy: 0.8628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 421/1875 [=====>........................] - ETA: 3s - loss: 0.3868 - accuracy: 0.8627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 445/1875 [======>.......................] - ETA: 3s - loss: 0.3850 - accuracy: 0.8638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 469/1875 [======>.......................] - ETA: 3s - loss: 0.3835 - 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\b\b\r",
      " 493/1875 [======>.......................] - ETA: 3s - loss: 0.3831 - accuracy: 0.8644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 516/1875 [=======>......................] - ETA: 2s - loss: 0.3842 - accuracy: 0.8638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 540/1875 [=======>......................] - ETA: 2s - loss: 0.3837 - 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\b\b\r",
      " 564/1875 [========>.....................] - ETA: 2s - loss: 0.3820 - accuracy: 0.8639"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 588/1875 [========>.....................] - ETA: 2s - loss: 0.3832 - accuracy: 0.8632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 612/1875 [========>.....................] - ETA: 2s - loss: 0.3816 - accuracy: 0.8638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 636/1875 [=========>....................] - ETA: 2s - loss: 0.3831 - accuracy: 0.8633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 660/1875 [=========>....................] - ETA: 2s - loss: 0.3827 - accuracy: 0.8634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 683/1875 [=========>....................] - ETA: 2s - loss: 0.3835 - accuracy: 0.8629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 706/1875 [==========>...................] - ETA: 2s - loss: 0.3831 - 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\b\b\r",
      " 730/1875 [==========>...................] - ETA: 2s - loss: 0.3835 - accuracy: 0.8628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 754/1875 [===========>..................] - ETA: 2s - loss: 0.3829 - accuracy: 0.8630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 777/1875 [===========>..................] - ETA: 2s - loss: 0.3833 - accuracy: 0.8629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 801/1875 [===========>..................] - ETA: 2s - loss: 0.3827 - accuracy: 0.8633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 825/1875 [============>.................] - ETA: 2s - loss: 0.3806 - 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\b\b\r",
      " 849/1875 [============>.................] - ETA: 2s - loss: 0.3813 - accuracy: 0.8640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 873/1875 [============>.................] - ETA: 2s - loss: 0.3801 - accuracy: 0.8644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 897/1875 [=============>................] - ETA: 2s - loss: 0.3809 - 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\b\b\r",
      " 921/1875 [=============>................] - ETA: 2s - loss: 0.3803 - accuracy: 0.8643"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 945/1875 [==============>...............] - ETA: 2s - loss: 0.3792 - accuracy: 0.8644"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 969/1875 [==============>...............] - ETA: 1s - loss: 0.3795 - accuracy: 0.8645"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 993/1875 [==============>...............] - ETA: 1s - loss: 0.3792 - accuracy: 0.8641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1017/1875 [===============>..............] - ETA: 1s - loss: 0.3783 - 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\b\b\r",
      "1041/1875 [===============>..............] - ETA: 1s - loss: 0.3792 - accuracy: 0.8647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1064/1875 [================>.............] - ETA: 1s - loss: 0.3794 - accuracy: 0.8644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1087/1875 [================>.............] - ETA: 1s - loss: 0.3805 - accuracy: 0.8637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1110/1875 [================>.............] - ETA: 1s - loss: 0.3806 - accuracy: 0.8634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1133/1875 [=================>............] - ETA: 1s - loss: 0.3799 - 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\b\b\r",
      "1157/1875 [=================>............] - ETA: 1s - loss: 0.3799 - accuracy: 0.8637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1181/1875 [=================>............] - ETA: 1s - loss: 0.3796 - accuracy: 0.8639"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1204/1875 [==================>...........] - ETA: 1s - loss: 0.3794 - accuracy: 0.8641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1228/1875 [==================>...........] - ETA: 1s - loss: 0.3795 - accuracy: 0.8640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1251/1875 [===================>..........] - ETA: 1s - loss: 0.3792 - 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\b\b\r",
      "1274/1875 [===================>..........] - ETA: 1s - loss: 0.3790 - accuracy: 0.8640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1298/1875 [===================>..........] - ETA: 1s - loss: 0.3790 - 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\b\b\r",
      "1322/1875 [====================>.........] - ETA: 1s - loss: 0.3794 - 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\b\b\r",
      "1346/1875 [====================>.........] - ETA: 1s - loss: 0.3787 - accuracy: 0.8638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1370/1875 [====================>.........] - ETA: 1s - loss: 0.3785 - accuracy: 0.8640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1394/1875 [=====================>........] - ETA: 1s - loss: 0.3781 - accuracy: 0.8639"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1418/1875 [=====================>........] - ETA: 0s - loss: 0.3777 - 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\b\b\r",
      "1442/1875 [======================>.......] - ETA: 0s - loss: 0.3773 - accuracy: 0.8643"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1465/1875 [======================>.......] - ETA: 0s - loss: 0.3768 - accuracy: 0.8645"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1875 [======================>.......] - ETA: 0s - loss: 0.3773 - 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\b\b\r",
      "1512/1875 [=======================>......] - ETA: 0s - loss: 0.3770 - accuracy: 0.8641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1536/1875 [=======================>......] - ETA: 0s - loss: 0.3784 - accuracy: 0.8635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1560/1875 [=======================>......] - ETA: 0s - loss: 0.3793 - accuracy: 0.8633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1585/1875 [========================>.....] - ETA: 0s - loss: 0.3788 - accuracy: 0.8633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1609/1875 [========================>.....] - ETA: 0s - loss: 0.3791 - accuracy: 0.8629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1634/1875 [=========================>....] - ETA: 0s - loss: 0.3793 - accuracy: 0.8630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1658/1875 [=========================>....] - ETA: 0s - loss: 0.3791 - accuracy: 0.8633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1682/1875 [=========================>....] - ETA: 0s - loss: 0.3791 - accuracy: 0.8633"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1706/1875 [==========================>...] - ETA: 0s - loss: 0.3801 - accuracy: 0.8627"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1730/1875 [==========================>...] - ETA: 0s - loss: 0.3801 - accuracy: 0.8628"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1753/1875 [===========================>..] - ETA: 0s - loss: 0.3804 - accuracy: 0.8629"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1777/1875 [===========================>..] - ETA: 0s - loss: 0.3797 - accuracy: 0.8630"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1801/1875 [===========================>..] - ETA: 0s - loss: 0.3787 - accuracy: 0.8634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1825/1875 [============================>.] - ETA: 0s - loss: 0.3786 - accuracy: 0.8635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1849/1875 [============================>.] - ETA: 0s - loss: 0.3783 - 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\b\b\r",
      "1872/1875 [============================>.] - ETA: 0s - loss: 0.3783 - 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\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.3784 - accuracy: 0.8636\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 4s - loss: 0.7461 - 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\b\b\r",
      "  25/1875 [..............................] - ETA: 3s - loss: 0.3887 - accuracy: 0.8450"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  49/1875 [..............................] - ETA: 3s - loss: 0.3797 - accuracy: 0.8552"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  72/1875 [>.............................] - ETA: 3s - loss: 0.3707 - accuracy: 0.8585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  95/1875 [>.............................] - ETA: 3s - loss: 0.3707 - accuracy: 0.8609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 118/1875 [>.............................] - ETA: 3s - loss: 0.3593 - accuracy: 0.8652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 142/1875 [=>............................] - ETA: 3s - loss: 0.3565 - accuracy: 0.8671"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 166/1875 [=>............................] - ETA: 3s - loss: 0.3528 - accuracy: 0.8682"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 190/1875 [==>...........................] - ETA: 3s - loss: 0.3598 - accuracy: 0.8683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 215/1875 [==>...........................] - ETA: 3s - loss: 0.3561 - 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\b\b\r",
      " 239/1875 [==>...........................] - ETA: 3s - loss: 0.3579 - accuracy: 0.8703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 264/1875 [===>..........................] - ETA: 3s - loss: 0.3563 - accuracy: 0.8709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 288/1875 [===>..........................] - ETA: 3s - loss: 0.3524 - accuracy: 0.8720"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 312/1875 [===>..........................] - ETA: 3s - loss: 0.3535 - accuracy: 0.8716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 337/1875 [====>.........................] - ETA: 3s - loss: 0.3536 - accuracy: 0.8725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 362/1875 [====>.........................] - ETA: 3s - loss: 0.3528 - accuracy: 0.8717"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 386/1875 [=====>........................] - ETA: 3s - loss: 0.3529 - 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\b\b\r",
      " 411/1875 [=====>........................] - ETA: 3s - loss: 0.3507 - accuracy: 0.8727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 436/1875 [=====>........................] - ETA: 3s - loss: 0.3487 - accuracy: 0.8736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 461/1875 [======>.......................] - ETA: 2s - loss: 0.3491 - accuracy: 0.8736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 486/1875 [======>.......................] - ETA: 2s - loss: 0.3476 - accuracy: 0.8745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 511/1875 [=======>......................] - ETA: 2s - loss: 0.3463 - accuracy: 0.8745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 535/1875 [=======>......................] - ETA: 2s - loss: 0.3466 - accuracy: 0.8746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 559/1875 [=======>......................] - ETA: 2s - loss: 0.3454 - accuracy: 0.8747"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 584/1875 [========>.....................] - ETA: 2s - loss: 0.3431 - accuracy: 0.8751"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 608/1875 [========>.....................] - ETA: 2s - loss: 0.3424 - accuracy: 0.8754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 633/1875 [=========>....................] - ETA: 2s - loss: 0.3433 - accuracy: 0.8742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 658/1875 [=========>....................] - ETA: 2s - loss: 0.3436 - accuracy: 0.8738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 683/1875 [=========>....................] - ETA: 2s - loss: 0.3421 - accuracy: 0.8739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 707/1875 [==========>...................] - ETA: 2s - loss: 0.3404 - accuracy: 0.8746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 731/1875 [==========>...................] - ETA: 2s - loss: 0.3403 - accuracy: 0.8747"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 755/1875 [===========>..................] - ETA: 2s - loss: 0.3390 - accuracy: 0.8753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 779/1875 [===========>..................] - ETA: 2s - loss: 0.3394 - accuracy: 0.8754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 804/1875 [===========>..................] - ETA: 2s - loss: 0.3405 - 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\b\b\r",
      " 829/1875 [============>.................] - ETA: 2s - loss: 0.3403 - accuracy: 0.8754"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 854/1875 [============>.................] - ETA: 2s - loss: 0.3410 - accuracy: 0.8753"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 879/1875 [=============>................] - ETA: 2s - loss: 0.3417 - accuracy: 0.8748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 904/1875 [=============>................] - ETA: 2s - loss: 0.3424 - accuracy: 0.8742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 928/1875 [=============>................] - ETA: 1s - loss: 0.3425 - accuracy: 0.8740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 952/1875 [==============>...............] - ETA: 1s - loss: 0.3429 - accuracy: 0.8740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1875 [==============>...............] - ETA: 1s - loss: 0.3428 - accuracy: 0.8738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1001/1875 [===============>..............] - ETA: 1s - loss: 0.3428 - accuracy: 0.8736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1026/1875 [===============>..............] - ETA: 1s - loss: 0.3439 - accuracy: 0.8733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1051/1875 [===============>..............] - ETA: 1s - loss: 0.3437 - accuracy: 0.8734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1075/1875 [================>.............] - ETA: 1s - loss: 0.3428 - accuracy: 0.8734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1099/1875 [================>.............] - ETA: 1s - loss: 0.3439 - accuracy: 0.8730"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1123/1875 [================>.............] - ETA: 1s - loss: 0.3432 - accuracy: 0.8733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1148/1875 [=================>............] - ETA: 1s - loss: 0.3428 - accuracy: 0.8734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1172/1875 [=================>............] - ETA: 1s - loss: 0.3423 - accuracy: 0.8735"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1196/1875 [==================>...........] - ETA: 1s - loss: 0.3427 - accuracy: 0.8736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1219/1875 [==================>...........] - ETA: 1s - loss: 0.3426 - accuracy: 0.8738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1243/1875 [==================>...........] - ETA: 1s - loss: 0.3427 - accuracy: 0.8738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1875 [===================>..........] - ETA: 1s - loss: 0.3424 - accuracy: 0.8738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1875 [===================>..........] - ETA: 1s - loss: 0.3423 - accuracy: 0.8739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1315/1875 [====================>.........] - ETA: 1s - loss: 0.3423 - accuracy: 0.8740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1339/1875 [====================>.........] - ETA: 1s - loss: 0.3419 - accuracy: 0.8743"
     ]
    },
    {
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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\r",
      "1363/1875 [====================>.........] - ETA: 1s - loss: 0.3418 - accuracy: 0.8743"
     ]
    },
    {
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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\r",
      "1387/1875 [=====================>........] - ETA: 1s - loss: 0.3413 - accuracy: 0.8744"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1411/1875 [=====================>........] - ETA: 0s - loss: 0.3410 - accuracy: 0.8745"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1434/1875 [=====================>........] - ETA: 0s - loss: 0.3409 - accuracy: 0.8747"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1458/1875 [======================>.......] - ETA: 0s - loss: 0.3413 - accuracy: 0.8744"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1482/1875 [======================>.......] - ETA: 0s - loss: 0.3421 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1506/1875 [=======================>......] - ETA: 0s - loss: 0.3421 - accuracy: 0.8739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1530/1875 [=======================>......] - ETA: 0s - loss: 0.3419 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1554/1875 [=======================>......] - ETA: 0s - loss: 0.3424 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1577/1875 [========================>.....] - ETA: 0s - loss: 0.3426 - accuracy: 0.8743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1600/1875 [========================>.....] - ETA: 0s - loss: 0.3431 - accuracy: 0.8742"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1624/1875 [========================>.....] - ETA: 0s - loss: 0.3431 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1648/1875 [=========================>....] - ETA: 0s - loss: 0.3426 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1671/1875 [=========================>....] - ETA: 0s - loss: 0.3422 - accuracy: 0.8745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1695/1875 [==========================>...] - ETA: 0s - loss: 0.3420 - accuracy: 0.8746"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1719/1875 [==========================>...] - ETA: 0s - loss: 0.3423 - accuracy: 0.8743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1743/1875 [==========================>...] - ETA: 0s - loss: 0.3426 - accuracy: 0.8743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1767/1875 [===========================>..] - ETA: 0s - loss: 0.3422 - accuracy: 0.8744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1791/1875 [===========================>..] - ETA: 0s - loss: 0.3424 - accuracy: 0.8743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1815/1875 [============================>.] - ETA: 0s - loss: 0.3429 - accuracy: 0.8741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1839/1875 [============================>.] - ETA: 0s - loss: 0.3422 - accuracy: 0.8744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1863/1875 [============================>.] - ETA: 0s - loss: 0.3422 - accuracy: 0.8744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.3419 - accuracy: 0.8745\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.2448 - accuracy: 0.9688"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  24/1875 [..............................] - ETA: 4s - loss: 0.2469 - accuracy: 0.9167"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  47/1875 [..............................] - ETA: 4s - loss: 0.3021 - accuracy: 0.8930"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  70/1875 [>.............................] - ETA: 4s - loss: 0.3026 - accuracy: 0.8960"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  93/1875 [>.............................] - ETA: 3s - loss: 0.3078 - accuracy: 0.8925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 117/1875 [>.............................] - ETA: 3s - loss: 0.3139 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1875 [=>............................] - ETA: 3s - loss: 0.3129 - accuracy: 0.8892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 164/1875 [=>............................] - ETA: 3s - loss: 0.3085 - accuracy: 0.8914"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 187/1875 [=>............................] - ETA: 3s - loss: 0.3101 - accuracy: 0.8902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 211/1875 [==>...........................] - ETA: 3s - loss: 0.3132 - 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\b\b\r",
      " 236/1875 [==>...........................] - ETA: 3s - loss: 0.3144 - accuracy: 0.8870"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 260/1875 [===>..........................] - ETA: 3s - loss: 0.3147 - accuracy: 0.8871"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 284/1875 [===>..........................] - ETA: 3s - loss: 0.3137 - accuracy: 0.8856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 309/1875 [===>..........................] - ETA: 3s - loss: 0.3158 - 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\b\b\r",
      " 334/1875 [====>.........................] - ETA: 3s - loss: 0.3124 - accuracy: 0.8859"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 359/1875 [====>.........................] - ETA: 3s - loss: 0.3154 - accuracy: 0.8851"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 383/1875 [=====>........................] - ETA: 3s - loss: 0.3168 - accuracy: 0.8841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 407/1875 [=====>........................] - ETA: 3s - loss: 0.3180 - accuracy: 0.8841"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 431/1875 [=====>........................] - ETA: 3s - loss: 0.3199 - accuracy: 0.8835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 455/1875 [======>.......................] - ETA: 3s - loss: 0.3202 - accuracy: 0.8830"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 479/1875 [======>.......................] - ETA: 2s - loss: 0.3212 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 503/1875 [=======>......................] - ETA: 2s - loss: 0.3228 - accuracy: 0.8821"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 526/1875 [=======>......................] - ETA: 2s - loss: 0.3234 - accuracy: 0.8814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 550/1875 [=======>......................] - ETA: 2s - loss: 0.3218 - accuracy: 0.8823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 575/1875 [========>.....................] - ETA: 2s - loss: 0.3232 - accuracy: 0.8825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 601/1875 [========>.....................] - ETA: 2s - loss: 0.3238 - accuracy: 0.8824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 625/1875 [=========>....................] - ETA: 2s - loss: 0.3249 - accuracy: 0.8820"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 649/1875 [=========>....................] - ETA: 2s - loss: 0.3242 - accuracy: 0.8824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 673/1875 [=========>....................] - ETA: 2s - loss: 0.3249 - accuracy: 0.8824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 698/1875 [==========>...................] - ETA: 2s - loss: 0.3250 - accuracy: 0.8823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 723/1875 [==========>...................] - ETA: 2s - loss: 0.3248 - accuracy: 0.8823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 747/1875 [==========>...................] - ETA: 2s - loss: 0.3238 - accuracy: 0.8825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 772/1875 [===========>..................] - ETA: 2s - loss: 0.3247 - accuracy: 0.8820"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1875 [===========>..................] - ETA: 2s - loss: 0.3246 - accuracy: 0.8819"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 820/1875 [============>.................] - ETA: 2s - loss: 0.3232 - accuracy: 0.8824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 844/1875 [============>.................] - ETA: 2s - loss: 0.3222 - accuracy: 0.8830"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 868/1875 [============>.................] - ETA: 2s - loss: 0.3229 - accuracy: 0.8828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 893/1875 [=============>................] - ETA: 2s - loss: 0.3215 - accuracy: 0.8828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 918/1875 [=============>................] - ETA: 2s - loss: 0.3201 - accuracy: 0.8834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 942/1875 [==============>...............] - ETA: 1s - loss: 0.3199 - accuracy: 0.8836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 966/1875 [==============>...............] - ETA: 1s - loss: 0.3191 - accuracy: 0.8838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 990/1875 [==============>...............] - ETA: 1s - loss: 0.3185 - accuracy: 0.8840"
     ]
    },
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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\r",
      "1014/1875 [===============>..............] - ETA: 1s - loss: 0.3183 - accuracy: 0.8839"
     ]
    },
    {
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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\r",
      "1037/1875 [===============>..............] - ETA: 1s - loss: 0.3183 - accuracy: 0.8835"
     ]
    },
    {
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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\r",
      "1061/1875 [===============>..............] - ETA: 1s - loss: 0.3166 - accuracy: 0.8840"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1085/1875 [================>.............] - ETA: 1s - loss: 0.3174 - accuracy: 0.8837"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1108/1875 [================>.............] - ETA: 1s - loss: 0.3183 - accuracy: 0.8833"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1131/1875 [=================>............] - ETA: 1s - loss: 0.3191 - accuracy: 0.8832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1154/1875 [=================>............] - ETA: 1s - loss: 0.3194 - accuracy: 0.8830"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1177/1875 [=================>............] - ETA: 1s - loss: 0.3200 - accuracy: 0.8826"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1200/1875 [==================>...........] - ETA: 1s - loss: 0.3199 - accuracy: 0.8829"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1223/1875 [==================>...........] - ETA: 1s - loss: 0.3203 - accuracy: 0.8828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1246/1875 [==================>...........] - ETA: 1s - loss: 0.3212 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1269/1875 [===================>..........] - ETA: 1s - loss: 0.3211 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1292/1875 [===================>..........] - ETA: 1s - loss: 0.3210 - accuracy: 0.8825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1315/1875 [====================>.........] - ETA: 1s - loss: 0.3206 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1338/1875 [====================>.........] - ETA: 1s - loss: 0.3205 - accuracy: 0.8823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1361/1875 [====================>.........] - ETA: 1s - loss: 0.3197 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1384/1875 [=====================>........] - ETA: 1s - loss: 0.3198 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1408/1875 [=====================>........] - ETA: 0s - loss: 0.3197 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1432/1875 [=====================>........] - ETA: 0s - loss: 0.3195 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1456/1875 [======================>.......] - ETA: 0s - loss: 0.3192 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1479/1875 [======================>.......] - ETA: 0s - loss: 0.3192 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1503/1875 [=======================>......] - ETA: 0s - loss: 0.3188 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1527/1875 [=======================>......] - ETA: 0s - loss: 0.3189 - accuracy: 0.8827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1551/1875 [=======================>......] - ETA: 0s - loss: 0.3190 - accuracy: 0.8825"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1575/1875 [========================>.....] - ETA: 0s - loss: 0.3183 - accuracy: 0.8826"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1599/1875 [========================>.....] - ETA: 0s - loss: 0.3180 - accuracy: 0.8826"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1622/1875 [========================>.....] - ETA: 0s - loss: 0.3176 - accuracy: 0.8827"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1646/1875 [=========================>....] - ETA: 0s - loss: 0.3174 - accuracy: 0.8827"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1669/1875 [=========================>....] - ETA: 0s - loss: 0.3173 - accuracy: 0.8828"
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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\b\b\r",
      "1692/1875 [==========================>...] - ETA: 0s - loss: 0.3172 - accuracy: 0.8826"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1716/1875 [==========================>...] - ETA: 0s - loss: 0.3168 - accuracy: 0.8830"
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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\b\b\r",
      "1740/1875 [==========================>...] - ETA: 0s - loss: 0.3160 - 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\b\b\r",
      "1764/1875 [===========================>..] - ETA: 0s - loss: 0.3157 - accuracy: 0.8835"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1788/1875 [===========================>..] - ETA: 0s - loss: 0.3162 - 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\b\b\r",
      "1812/1875 [===========================>..] - ETA: 0s - loss: 0.3162 - accuracy: 0.8834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1836/1875 [============================>.] - ETA: 0s - loss: 0.3158 - accuracy: 0.8836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1860/1875 [============================>.] - ETA: 0s - loss: 0.3158 - accuracy: 0.8836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.3157 - accuracy: 0.8838\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.1672 - accuracy: 0.9375"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  24/1875 [..............................] - ETA: 4s - loss: 0.2605 - accuracy: 0.8984"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  48/1875 [..............................] - ETA: 3s - loss: 0.2845 - accuracy: 0.8932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  72/1875 [>.............................] - ETA: 3s - loss: 0.2849 - accuracy: 0.8928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  95/1875 [>.............................] - ETA: 3s - loss: 0.2853 - accuracy: 0.8928"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 119/1875 [>.............................] - ETA: 3s - loss: 0.2823 - accuracy: 0.8942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 143/1875 [=>............................] - ETA: 3s - loss: 0.2825 - accuracy: 0.8936"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 167/1875 [=>............................] - ETA: 3s - loss: 0.2854 - accuracy: 0.8924"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 191/1875 [==>...........................] - ETA: 3s - loss: 0.2843 - accuracy: 0.8932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 215/1875 [==>...........................] - ETA: 3s - loss: 0.2864 - accuracy: 0.8929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 239/1875 [==>...........................] - ETA: 3s - loss: 0.2898 - accuracy: 0.8903"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 262/1875 [===>..........................] - ETA: 3s - loss: 0.2880 - accuracy: 0.8912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 285/1875 [===>..........................] - ETA: 3s - loss: 0.2894 - accuracy: 0.8909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 308/1875 [===>..........................] - ETA: 3s - loss: 0.2910 - accuracy: 0.8902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 332/1875 [====>.........................] - ETA: 3s - loss: 0.2912 - accuracy: 0.8902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 356/1875 [====>.........................] - ETA: 3s - loss: 0.2938 - accuracy: 0.8890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 380/1875 [=====>........................] - ETA: 3s - loss: 0.2960 - accuracy: 0.8884"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 404/1875 [=====>........................] - ETA: 3s - loss: 0.2933 - accuracy: 0.8892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 427/1875 [=====>........................] - ETA: 3s - loss: 0.2955 - accuracy: 0.8891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 451/1875 [======>.......................] - ETA: 3s - loss: 0.2945 - accuracy: 0.8899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 475/1875 [======>.......................] - ETA: 3s - loss: 0.2937 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 499/1875 [======>.......................] - ETA: 2s - loss: 0.2932 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 522/1875 [=======>......................] - ETA: 2s - loss: 0.2938 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 546/1875 [=======>......................] - ETA: 2s - loss: 0.2936 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 570/1875 [========>.....................] - ETA: 2s - loss: 0.2957 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 594/1875 [========>.....................] - ETA: 2s - loss: 0.2967 - accuracy: 0.8892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 618/1875 [========>.....................] - ETA: 2s - loss: 0.2972 - accuracy: 0.8891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 642/1875 [=========>....................] - ETA: 2s - loss: 0.2969 - accuracy: 0.8890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1875 [=========>....................] - ETA: 2s - loss: 0.2958 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 691/1875 [==========>...................] - ETA: 2s - loss: 0.2962 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 716/1875 [==========>...................] - ETA: 2s - loss: 0.2989 - accuracy: 0.8886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 741/1875 [==========>...................] - ETA: 2s - loss: 0.2985 - accuracy: 0.8891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 765/1875 [===========>..................] - ETA: 2s - loss: 0.2987 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 788/1875 [===========>..................] - ETA: 2s - loss: 0.2993 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 812/1875 [===========>..................] - ETA: 2s - loss: 0.2990 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 836/1875 [============>.................] - ETA: 2s - loss: 0.2984 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 859/1875 [============>.................] - ETA: 2s - loss: 0.2984 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 882/1875 [=============>................] - ETA: 2s - loss: 0.2977 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 905/1875 [=============>................] - ETA: 2s - loss: 0.2984 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 928/1875 [=============>................] - ETA: 2s - loss: 0.2993 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 952/1875 [==============>...............] - ETA: 1s - loss: 0.3004 - accuracy: 0.8893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1875 [==============>...............] - ETA: 1s - loss: 0.3005 - accuracy: 0.8891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1000/1875 [===============>..............] - ETA: 1s - loss: 0.3003 - accuracy: 0.8892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1024/1875 [===============>..............] - ETA: 1s - loss: 0.2998 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1048/1875 [===============>..............] - ETA: 1s - loss: 0.2994 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1072/1875 [================>.............] - ETA: 1s - loss: 0.3003 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1096/1875 [================>.............] - ETA: 1s - loss: 0.3002 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1875 [================>.............] - ETA: 1s - loss: 0.2996 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1143/1875 [=================>............] - ETA: 1s - loss: 0.2987 - accuracy: 0.8899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1167/1875 [=================>............] - ETA: 1s - loss: 0.2993 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1191/1875 [==================>...........] - ETA: 1s - loss: 0.2991 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1214/1875 [==================>...........] - ETA: 1s - loss: 0.2989 - accuracy: 0.8899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1238/1875 [==================>...........] - ETA: 1s - loss: 0.2992 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1262/1875 [===================>..........] - ETA: 1s - loss: 0.2992 - accuracy: 0.8899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1285/1875 [===================>..........] - ETA: 1s - loss: 0.2993 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1309/1875 [===================>..........] - ETA: 1s - loss: 0.2997 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1333/1875 [====================>.........] - ETA: 1s - loss: 0.3002 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1357/1875 [====================>.........] - ETA: 1s - loss: 0.2995 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1381/1875 [=====================>........] - ETA: 1s - loss: 0.2996 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1405/1875 [=====================>........] - ETA: 1s - loss: 0.2996 - accuracy: 0.8895"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1428/1875 [=====================>........] - ETA: 0s - loss: 0.2990 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1451/1875 [======================>.......] - ETA: 0s - loss: 0.2990 - accuracy: 0.8895"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1475/1875 [======================>.......] - ETA: 0s - loss: 0.2984 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1499/1875 [======================>.......] - ETA: 0s - loss: 0.2993 - accuracy: 0.8893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1523/1875 [=======================>......] - ETA: 0s - loss: 0.2990 - accuracy: 0.8893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1547/1875 [=======================>......] - ETA: 0s - loss: 0.2996 - accuracy: 0.8893"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1571/1875 [========================>.....] - ETA: 0s - loss: 0.2990 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1595/1875 [========================>.....] - ETA: 0s - loss: 0.2991 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1620/1875 [========================>.....] - ETA: 0s - loss: 0.2995 - accuracy: 0.8894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1644/1875 [=========================>....] - ETA: 0s - loss: 0.2988 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1668/1875 [=========================>....] - ETA: 0s - loss: 0.2985 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1692/1875 [==========================>...] - ETA: 0s - loss: 0.2978 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1716/1875 [==========================>...] - ETA: 0s - loss: 0.2982 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1740/1875 [==========================>...] - ETA: 0s - loss: 0.2982 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1765/1875 [===========================>..] - ETA: 0s - loss: 0.2980 - accuracy: 0.8897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1790/1875 [===========================>..] - ETA: 0s - loss: 0.2974 - accuracy: 0.8899"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1814/1875 [============================>.] - ETA: 0s - loss: 0.2985 - accuracy: 0.8896"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1838/1875 [============================>.] - ETA: 0s - loss: 0.2988 - accuracy: 0.8895"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1862/1875 [============================>.] - ETA: 0s - loss: 0.2992 - accuracy: 0.8892"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2996 - accuracy: 0.8889\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.2643 - 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\b\b\r",
      "  26/1875 [..............................] - ETA: 3s - loss: 0.2754 - accuracy: 0.9002"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  50/1875 [..............................] - ETA: 3s - loss: 0.2696 - accuracy: 0.9031"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  74/1875 [>.............................] - ETA: 3s - loss: 0.2797 - accuracy: 0.8965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  98/1875 [>.............................] - ETA: 3s - loss: 0.2901 - accuracy: 0.8909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1875 [>.............................] - ETA: 3s - loss: 0.2878 - accuracy: 0.8906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 146/1875 [=>............................] - ETA: 3s - loss: 0.2929 - accuracy: 0.8898"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 170/1875 [=>............................] - ETA: 3s - loss: 0.2930 - accuracy: 0.8906"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 194/1875 [==>...........................] - ETA: 3s - loss: 0.2871 - accuracy: 0.8926"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 219/1875 [==>...........................] - ETA: 3s - loss: 0.2846 - accuracy: 0.8944"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 243/1875 [==>...........................] - ETA: 3s - loss: 0.2860 - accuracy: 0.8942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 267/1875 [===>..........................] - ETA: 3s - loss: 0.2868 - accuracy: 0.8942"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 291/1875 [===>..........................] - ETA: 3s - loss: 0.2866 - accuracy: 0.8951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 315/1875 [====>.........................] - ETA: 3s - loss: 0.2834 - accuracy: 0.8958"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 339/1875 [====>.........................] - ETA: 3s - loss: 0.2854 - accuracy: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 363/1875 [====>.........................] - ETA: 3s - loss: 0.2845 - accuracy: 0.8957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 387/1875 [=====>........................] - ETA: 3s - loss: 0.2856 - accuracy: 0.8958"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 410/1875 [=====>........................] - ETA: 3s - loss: 0.2841 - accuracy: 0.8965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 434/1875 [=====>........................] - ETA: 3s - loss: 0.2855 - accuracy: 0.8961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 458/1875 [======>.......................] - ETA: 3s - loss: 0.2842 - accuracy: 0.8964"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 482/1875 [======>.......................] - ETA: 2s - loss: 0.2842 - accuracy: 0.8962"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 507/1875 [=======>......................] - ETA: 2s - loss: 0.2848 - accuracy: 0.8956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 532/1875 [=======>......................] - ETA: 2s - loss: 0.2873 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 556/1875 [=======>......................] - ETA: 2s - loss: 0.2882 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 581/1875 [========>.....................] - ETA: 2s - loss: 0.2883 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 605/1875 [========>.....................] - ETA: 2s - loss: 0.2878 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 629/1875 [=========>....................] - ETA: 2s - loss: 0.2872 - accuracy: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 653/1875 [=========>....................] - ETA: 2s - loss: 0.2873 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 678/1875 [=========>....................] - ETA: 2s - loss: 0.2874 - accuracy: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 702/1875 [==========>...................] - ETA: 2s - loss: 0.2880 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 726/1875 [==========>...................] - ETA: 2s - loss: 0.2868 - accuracy: 0.8951"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 751/1875 [===========>..................] - ETA: 2s - loss: 0.2857 - accuracy: 0.8957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 776/1875 [===========>..................] - ETA: 2s - loss: 0.2853 - accuracy: 0.8959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 800/1875 [===========>..................] - ETA: 2s - loss: 0.2850 - accuracy: 0.8959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 825/1875 [============>.................] - ETA: 2s - loss: 0.2846 - accuracy: 0.8958"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 849/1875 [============>.................] - ETA: 2s - loss: 0.2850 - accuracy: 0.8957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 873/1875 [============>.................] - ETA: 2s - loss: 0.2851 - accuracy: 0.8957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 898/1875 [=============>................] - ETA: 2s - loss: 0.2842 - accuracy: 0.8960"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 922/1875 [=============>................] - ETA: 2s - loss: 0.2840 - accuracy: 0.8960"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1875 [==============>...............] - ETA: 1s - loss: 0.2836 - accuracy: 0.8959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 970/1875 [==============>...............] - ETA: 1s - loss: 0.2829 - accuracy: 0.8962"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 994/1875 [==============>...............] - ETA: 1s - loss: 0.2828 - accuracy: 0.8961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1019/1875 [===============>..............] - ETA: 1s - loss: 0.2836 - accuracy: 0.8957"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1043/1875 [===============>..............] - ETA: 1s - loss: 0.2835 - accuracy: 0.8957"
     ]
    },
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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\r",
      "1067/1875 [================>.............] - ETA: 1s - loss: 0.2834 - accuracy: 0.8958"
     ]
    },
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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\r",
      "1092/1875 [================>.............] - ETA: 1s - loss: 0.2839 - accuracy: 0.8959"
     ]
    },
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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\r",
      "1117/1875 [================>.............] - ETA: 1s - loss: 0.2844 - accuracy: 0.8955"
     ]
    },
    {
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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\r",
      "1142/1875 [=================>............] - ETA: 1s - loss: 0.2843 - accuracy: 0.8956"
     ]
    },
    {
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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\r",
      "1167/1875 [=================>............] - ETA: 1s - loss: 0.2843 - accuracy: 0.8956"
     ]
    },
    {
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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\r",
      "1192/1875 [==================>...........] - ETA: 1s - loss: 0.2840 - accuracy: 0.8956"
     ]
    },
    {
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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\r",
      "1216/1875 [==================>...........] - ETA: 1s - loss: 0.2853 - accuracy: 0.8954"
     ]
    },
    {
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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\r",
      "1241/1875 [==================>...........] - ETA: 1s - loss: 0.2848 - accuracy: 0.8954"
     ]
    },
    {
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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\r",
      "1266/1875 [===================>..........] - ETA: 1s - loss: 0.2848 - accuracy: 0.8951"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1875 [===================>..........] - ETA: 1s - loss: 0.2856 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1316/1875 [====================>.........] - ETA: 1s - loss: 0.2853 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1341/1875 [====================>.........] - ETA: 1s - loss: 0.2856 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1366/1875 [====================>.........] - ETA: 1s - loss: 0.2853 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1391/1875 [=====================>........] - ETA: 1s - loss: 0.2846 - accuracy: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1416/1875 [=====================>........] - ETA: 0s - loss: 0.2840 - accuracy: 0.8952"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1442/1875 [======================>.......] - ETA: 0s - loss: 0.2849 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1875 [======================>.......] - ETA: 0s - loss: 0.2848 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1492/1875 [======================>.......] - ETA: 0s - loss: 0.2843 - accuracy: 0.8950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1517/1875 [=======================>......] - ETA: 0s - loss: 0.2845 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1542/1875 [=======================>......] - ETA: 0s - loss: 0.2842 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1567/1875 [========================>.....] - ETA: 0s - loss: 0.2843 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1591/1875 [========================>.....] - ETA: 0s - loss: 0.2842 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1616/1875 [========================>.....] - ETA: 0s - loss: 0.2849 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1641/1875 [=========================>....] - ETA: 0s - loss: 0.2846 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1666/1875 [=========================>....] - ETA: 0s - loss: 0.2840 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1691/1875 [==========================>...] - ETA: 0s - loss: 0.2838 - accuracy: 0.8949"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1716/1875 [==========================>...] - ETA: 0s - loss: 0.2836 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1740/1875 [==========================>...] - ETA: 0s - loss: 0.2839 - accuracy: 0.8946"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1764/1875 [===========================>..] - ETA: 0s - loss: 0.2836 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1789/1875 [===========================>..] - ETA: 0s - loss: 0.2831 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1814/1875 [============================>.] - ETA: 0s - loss: 0.2829 - accuracy: 0.8949"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1839/1875 [============================>.] - ETA: 0s - loss: 0.2831 - accuracy: 0.8949"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1864/1875 [============================>.] - ETA: 0s - loss: 0.2831 - accuracy: 0.8948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2831 - accuracy: 0.8948\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.1719 - accuracy: 0.9375"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  26/1875 [..............................] - ETA: 3s - loss: 0.2540 - accuracy: 0.9014"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  50/1875 [..............................] - ETA: 3s - loss: 0.2485 - accuracy: 0.9069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  74/1875 [>.............................] - ETA: 3s - loss: 0.2452 - accuracy: 0.9084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  98/1875 [>.............................] - ETA: 3s - loss: 0.2481 - accuracy: 0.9072"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 123/1875 [>.............................] - ETA: 3s - loss: 0.2510 - accuracy: 0.9068"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 147/1875 [=>............................] - ETA: 3s - loss: 0.2596 - accuracy: 0.9037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 172/1875 [=>............................] - ETA: 3s - loss: 0.2557 - accuracy: 0.9052"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 195/1875 [==>...........................] - ETA: 3s - loss: 0.2574 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 219/1875 [==>...........................] - ETA: 3s - loss: 0.2616 - accuracy: 0.9003"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 244/1875 [==>...........................] - ETA: 3s - loss: 0.2659 - accuracy: 0.8986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 269/1875 [===>..........................] - ETA: 3s - loss: 0.2656 - accuracy: 0.8993"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 294/1875 [===>..........................] - ETA: 3s - loss: 0.2639 - accuracy: 0.8998"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 319/1875 [====>.........................] - ETA: 3s - loss: 0.2632 - accuracy: 0.9003"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 344/1875 [====>.........................] - ETA: 3s - loss: 0.2622 - accuracy: 0.9007"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 369/1875 [====>.........................] - ETA: 3s - loss: 0.2632 - accuracy: 0.9012"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 393/1875 [=====>........................] - ETA: 3s - loss: 0.2637 - accuracy: 0.9015"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 418/1875 [=====>........................] - ETA: 3s - loss: 0.2632 - accuracy: 0.9020"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 443/1875 [======>.......................] - ETA: 2s - loss: 0.2652 - accuracy: 0.9012"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 468/1875 [======>.......................] - ETA: 2s - loss: 0.2655 - accuracy: 0.9006"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 494/1875 [======>.......................] - ETA: 2s - loss: 0.2653 - accuracy: 0.9011"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 519/1875 [=======>......................] - ETA: 2s - loss: 0.2656 - accuracy: 0.9010"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 544/1875 [=======>......................] - ETA: 2s - loss: 0.2664 - accuracy: 0.9007"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 568/1875 [========>.....................] - ETA: 2s - loss: 0.2681 - accuracy: 0.9001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 592/1875 [========>.....................] - ETA: 2s - loss: 0.2692 - 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\b\b\r",
      " 616/1875 [========>.....................] - ETA: 2s - loss: 0.2712 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 641/1875 [=========>....................] - ETA: 2s - loss: 0.2706 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1875 [=========>....................] - ETA: 2s - loss: 0.2718 - accuracy: 0.8981"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 690/1875 [==========>...................] - ETA: 2s - loss: 0.2705 - accuracy: 0.8989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 715/1875 [==========>...................] - ETA: 2s - loss: 0.2707 - accuracy: 0.8985"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 740/1875 [==========>...................] - ETA: 2s - loss: 0.2714 - accuracy: 0.8984"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 766/1875 [===========>..................] - ETA: 2s - loss: 0.2716 - accuracy: 0.8986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 791/1875 [===========>..................] - ETA: 2s - loss: 0.2718 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 815/1875 [============>.................] - ETA: 2s - loss: 0.2711 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 840/1875 [============>.................] - ETA: 2s - loss: 0.2700 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 865/1875 [============>.................] - ETA: 2s - loss: 0.2701 - accuracy: 0.8991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 890/1875 [=============>................] - ETA: 2s - loss: 0.2718 - accuracy: 0.8986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 915/1875 [=============>................] - ETA: 1s - loss: 0.2719 - accuracy: 0.8986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 940/1875 [==============>...............] - ETA: 1s - loss: 0.2706 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 964/1875 [==============>...............] - ETA: 1s - loss: 0.2702 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 989/1875 [==============>...............] - ETA: 1s - loss: 0.2704 - accuracy: 0.8991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1014/1875 [===============>..............] - ETA: 1s - loss: 0.2703 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1039/1875 [===============>..............] - ETA: 1s - loss: 0.2708 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1064/1875 [================>.............] - ETA: 1s - loss: 0.2694 - accuracy: 0.8994"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1089/1875 [================>.............] - ETA: 1s - loss: 0.2702 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1114/1875 [================>.............] - ETA: 1s - loss: 0.2707 - accuracy: 0.8989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1139/1875 [=================>............] - ETA: 1s - loss: 0.2706 - accuracy: 0.8989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1163/1875 [=================>............] - ETA: 1s - loss: 0.2706 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1188/1875 [==================>...........] - ETA: 1s - loss: 0.2707 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1214/1875 [==================>...........] - ETA: 1s - loss: 0.2713 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1240/1875 [==================>...........] - ETA: 1s - loss: 0.2713 - accuracy: 0.8991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1266/1875 [===================>..........] - ETA: 1s - loss: 0.2713 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1875 [===================>..........] - ETA: 1s - loss: 0.2712 - accuracy: 0.8989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1316/1875 [====================>.........] - ETA: 1s - loss: 0.2709 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1341/1875 [====================>.........] - ETA: 1s - loss: 0.2712 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1366/1875 [====================>.........] - ETA: 1s - loss: 0.2712 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1390/1875 [=====================>........] - ETA: 0s - loss: 0.2709 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1414/1875 [=====================>........] - ETA: 0s - loss: 0.2711 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1438/1875 [======================>.......] - ETA: 0s - loss: 0.2710 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1463/1875 [======================>.......] - ETA: 0s - loss: 0.2707 - accuracy: 0.8991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1875 [======================>.......] - ETA: 0s - loss: 0.2707 - accuracy: 0.8992"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1514/1875 [=======================>......] - ETA: 0s - loss: 0.2710 - accuracy: 0.8991"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1540/1875 [=======================>......] - ETA: 0s - loss: 0.2715 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1565/1875 [========================>.....] - ETA: 0s - loss: 0.2716 - accuracy: 0.8985"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1591/1875 [========================>.....] - ETA: 0s - loss: 0.2725 - accuracy: 0.8980"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1617/1875 [========================>.....] - ETA: 0s - loss: 0.2720 - accuracy: 0.8982"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1643/1875 [=========================>....] - ETA: 0s - loss: 0.2722 - accuracy: 0.8981"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1668/1875 [=========================>....] - ETA: 0s - loss: 0.2714 - accuracy: 0.8985"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1693/1875 [==========================>...] - ETA: 0s - loss: 0.2715 - accuracy: 0.8985"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1718/1875 [==========================>...] - ETA: 0s - loss: 0.2714 - accuracy: 0.8986"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1743/1875 [==========================>...] - ETA: 0s - loss: 0.2710 - accuracy: 0.8987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1768/1875 [===========================>..] - ETA: 0s - loss: 0.2710 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1793/1875 [===========================>..] - ETA: 0s - loss: 0.2708 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1818/1875 [============================>.] - ETA: 0s - loss: 0.2706 - accuracy: 0.8988"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1842/1875 [============================>.] - ETA: 0s - loss: 0.2703 - accuracy: 0.8990"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1867/1875 [============================>.] - ETA: 0s - loss: 0.2701 - accuracy: 0.8989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2700 - accuracy: 0.8989\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 4s - loss: 0.6528 - 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\b\b\r",
      "  25/1875 [..............................] - ETA: 3s - loss: 0.2575 - accuracy: 0.9075"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  49/1875 [..............................] - ETA: 3s - loss: 0.2556 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  74/1875 [>.............................] - ETA: 3s - loss: 0.2675 - accuracy: 0.9071"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  99/1875 [>.............................] - ETA: 3s - loss: 0.2685 - accuracy: 0.9028"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 123/1875 [>.............................] - ETA: 3s - loss: 0.2643 - accuracy: 0.9027"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 148/1875 [=>............................] - ETA: 3s - loss: 0.2706 - accuracy: 0.8997"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 173/1875 [=>............................] - ETA: 3s - loss: 0.2709 - accuracy: 0.8985"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 198/1875 [==>...........................] - ETA: 3s - loss: 0.2668 - accuracy: 0.9001"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 222/1875 [==>...........................] - ETA: 3s - loss: 0.2618 - accuracy: 0.9017"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 246/1875 [==>...........................] - ETA: 3s - loss: 0.2609 - accuracy: 0.9019"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 270/1875 [===>..........................] - ETA: 3s - loss: 0.2610 - accuracy: 0.9014"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 295/1875 [===>..........................] - ETA: 3s - loss: 0.2608 - accuracy: 0.9023"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 320/1875 [====>.........................] - ETA: 3s - loss: 0.2569 - accuracy: 0.9046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 345/1875 [====>.........................] - ETA: 3s - loss: 0.2545 - accuracy: 0.9054"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 370/1875 [====>.........................] - ETA: 3s - loss: 0.2528 - accuracy: 0.9068"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 395/1875 [=====>........................] - ETA: 3s - loss: 0.2523 - accuracy: 0.9071"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 421/1875 [=====>........................] - ETA: 3s - loss: 0.2545 - accuracy: 0.9061"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 446/1875 [======>.......................] - ETA: 2s - loss: 0.2535 - accuracy: 0.9064"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 471/1875 [======>.......................] - ETA: 2s - loss: 0.2524 - accuracy: 0.9073"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 496/1875 [======>.......................] - ETA: 2s - loss: 0.2519 - accuracy: 0.9076"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 521/1875 [=======>......................] - ETA: 2s - loss: 0.2517 - accuracy: 0.9077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 546/1875 [=======>......................] - ETA: 2s - loss: 0.2535 - accuracy: 0.9077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 572/1875 [========>.....................] - ETA: 2s - loss: 0.2534 - accuracy: 0.9076"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 598/1875 [========>.....................] - ETA: 2s - loss: 0.2536 - accuracy: 0.9072"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 623/1875 [========>.....................] - ETA: 2s - loss: 0.2546 - accuracy: 0.9074"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 649/1875 [=========>....................] - ETA: 2s - loss: 0.2563 - accuracy: 0.9067"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 674/1875 [=========>....................] - ETA: 2s - loss: 0.2557 - accuracy: 0.9066"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 700/1875 [==========>...................] - ETA: 2s - loss: 0.2575 - accuracy: 0.9060"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 725/1875 [==========>...................] - ETA: 2s - loss: 0.2576 - accuracy: 0.9056"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 750/1875 [===========>..................] - ETA: 2s - loss: 0.2587 - accuracy: 0.9050"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 775/1875 [===========>..................] - ETA: 2s - loss: 0.2587 - accuracy: 0.9048"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 800/1875 [===========>..................] - ETA: 2s - loss: 0.2587 - accuracy: 0.9047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 826/1875 [============>.................] - ETA: 2s - loss: 0.2568 - accuracy: 0.9052"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 852/1875 [============>.................] - ETA: 2s - loss: 0.2567 - accuracy: 0.9049"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 877/1875 [=============>................] - ETA: 2s - loss: 0.2568 - accuracy: 0.9049"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 902/1875 [=============>................] - ETA: 1s - loss: 0.2586 - accuracy: 0.9042"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 927/1875 [=============>................] - ETA: 1s - loss: 0.2578 - accuracy: 0.9045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 952/1875 [==============>...............] - ETA: 1s - loss: 0.2578 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1875 [==============>...............] - ETA: 1s - loss: 0.2586 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1001/1875 [===============>..............] - ETA: 1s - loss: 0.2580 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1025/1875 [===============>..............] - ETA: 1s - loss: 0.2576 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1050/1875 [===============>..............] - ETA: 1s - loss: 0.2575 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1075/1875 [================>.............] - ETA: 1s - loss: 0.2584 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1100/1875 [================>.............] - ETA: 1s - loss: 0.2591 - accuracy: 0.9037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1124/1875 [================>.............] - ETA: 1s - loss: 0.2592 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1148/1875 [=================>............] - ETA: 1s - loss: 0.2589 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1172/1875 [=================>............] - ETA: 1s - loss: 0.2590 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1196/1875 [==================>...........] - ETA: 1s - loss: 0.2589 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1221/1875 [==================>...........] - ETA: 1s - loss: 0.2590 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1246/1875 [==================>...........] - ETA: 1s - loss: 0.2596 - accuracy: 0.9039"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1270/1875 [===================>..........] - ETA: 1s - loss: 0.2591 - accuracy: 0.9038"
     ]
    },
    {
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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\r",
      "1294/1875 [===================>..........] - ETA: 1s - loss: 0.2586 - accuracy: 0.9041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1318/1875 [====================>.........] - ETA: 1s - loss: 0.2585 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1343/1875 [====================>.........] - ETA: 1s - loss: 0.2579 - accuracy: 0.9043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1367/1875 [====================>.........] - ETA: 1s - loss: 0.2575 - accuracy: 0.9042"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1391/1875 [=====================>........] - ETA: 0s - loss: 0.2580 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1415/1875 [=====================>........] - ETA: 0s - loss: 0.2584 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1440/1875 [======================>.......] - ETA: 0s - loss: 0.2586 - accuracy: 0.9037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1464/1875 [======================>.......] - ETA: 0s - loss: 0.2584 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1489/1875 [======================>.......] - ETA: 0s - loss: 0.2583 - accuracy: 0.9041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1513/1875 [=======================>......] - ETA: 0s - loss: 0.2585 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1538/1875 [=======================>......] - ETA: 0s - loss: 0.2583 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1563/1875 [========================>.....] - ETA: 0s - loss: 0.2581 - accuracy: 0.9041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1588/1875 [========================>.....] - ETA: 0s - loss: 0.2582 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1612/1875 [========================>.....] - ETA: 0s - loss: 0.2586 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1636/1875 [=========================>....] - ETA: 0s - loss: 0.2588 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1660/1875 [=========================>....] - ETA: 0s - loss: 0.2584 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1683/1875 [=========================>....] - ETA: 0s - loss: 0.2581 - accuracy: 0.9041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1706/1875 [==========================>...] - ETA: 0s - loss: 0.2583 - accuracy: 0.9040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1730/1875 [==========================>...] - ETA: 0s - loss: 0.2583 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1754/1875 [===========================>..] - ETA: 0s - loss: 0.2578 - accuracy: 0.9042"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1778/1875 [===========================>..] - ETA: 0s - loss: 0.2582 - accuracy: 0.9039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1802/1875 [===========================>..] - ETA: 0s - loss: 0.2584 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1826/1875 [============================>.] - ETA: 0s - loss: 0.2584 - accuracy: 0.9037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1850/1875 [============================>.] - ETA: 0s - loss: 0.2583 - accuracy: 0.9037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2583 - accuracy: 0.9038\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.2861 - accuracy: 0.8438"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  26/1875 [..............................] - ETA: 3s - loss: 0.2714 - accuracy: 0.8966"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  51/1875 [..............................] - ETA: 3s - loss: 0.2666 - accuracy: 0.9038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  76/1875 [>.............................] - ETA: 3s - loss: 0.2576 - accuracy: 0.9021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1875 [>.............................] - ETA: 3s - loss: 0.2516 - accuracy: 0.9047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1875 [=>............................] - ETA: 3s - loss: 0.2513 - accuracy: 0.9058"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 151/1875 [=>............................] - ETA: 3s - loss: 0.2482 - accuracy: 0.9077"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 176/1875 [=>............................] - ETA: 3s - loss: 0.2482 - accuracy: 0.9070"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 201/1875 [==>...........................] - ETA: 3s - loss: 0.2485 - accuracy: 0.9070"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 224/1875 [==>...........................] - ETA: 3s - loss: 0.2517 - accuracy: 0.9056"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 248/1875 [==>...........................] - ETA: 3s - loss: 0.2483 - accuracy: 0.9069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 273/1875 [===>..........................] - ETA: 3s - loss: 0.2488 - accuracy: 0.9069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 297/1875 [===>..........................] - ETA: 3s - loss: 0.2489 - accuracy: 0.9076"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 320/1875 [====>.........................] - ETA: 3s - loss: 0.2475 - accuracy: 0.9084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 345/1875 [====>.........................] - ETA: 3s - loss: 0.2472 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 370/1875 [====>.........................] - ETA: 3s - loss: 0.2465 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 395/1875 [=====>........................] - ETA: 3s - loss: 0.2457 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 419/1875 [=====>........................] - ETA: 3s - loss: 0.2458 - 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\b\b\r",
      " 443/1875 [======>.......................] - ETA: 2s - loss: 0.2452 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 468/1875 [======>.......................] - ETA: 2s - loss: 0.2421 - accuracy: 0.9109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 494/1875 [======>.......................] - ETA: 2s - loss: 0.2418 - accuracy: 0.9111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 519/1875 [=======>......................] - ETA: 2s - loss: 0.2417 - accuracy: 0.9114"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 544/1875 [=======>......................] - ETA: 2s - loss: 0.2429 - accuracy: 0.9111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 569/1875 [========>.....................] - ETA: 2s - loss: 0.2427 - accuracy: 0.9115"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 593/1875 [========>.....................] - ETA: 2s - loss: 0.2434 - accuracy: 0.9113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 618/1875 [========>.....................] - ETA: 2s - loss: 0.2430 - accuracy: 0.9116"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 643/1875 [=========>....................] - ETA: 2s - loss: 0.2444 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 668/1875 [=========>....................] - ETA: 2s - loss: 0.2442 - accuracy: 0.9113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 694/1875 [==========>...................] - ETA: 2s - loss: 0.2449 - accuracy: 0.9109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 720/1875 [==========>...................] - ETA: 2s - loss: 0.2447 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 745/1875 [==========>...................] - ETA: 2s - loss: 0.2434 - accuracy: 0.9111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 771/1875 [===========>..................] - ETA: 2s - loss: 0.2420 - accuracy: 0.9116"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1875 [===========>..................] - ETA: 2s - loss: 0.2416 - accuracy: 0.9115"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 821/1875 [============>.................] - ETA: 2s - loss: 0.2430 - accuracy: 0.9110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 846/1875 [============>.................] - ETA: 2s - loss: 0.2424 - accuracy: 0.9112"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 871/1875 [============>.................] - ETA: 2s - loss: 0.2425 - accuracy: 0.9110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 896/1875 [=============>................] - ETA: 2s - loss: 0.2424 - accuracy: 0.9111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 921/1875 [=============>................] - ETA: 1s - loss: 0.2428 - accuracy: 0.9109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 945/1875 [==============>...............] - ETA: 1s - loss: 0.2438 - accuracy: 0.9104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 969/1875 [==============>...............] - ETA: 1s - loss: 0.2434 - accuracy: 0.9105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 993/1875 [==============>...............] - ETA: 1s - loss: 0.2426 - accuracy: 0.9107"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1018/1875 [===============>..............] - ETA: 1s - loss: 0.2423 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1043/1875 [===============>..............] - ETA: 1s - loss: 0.2426 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1875 [================>.............] - ETA: 1s - loss: 0.2429 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1093/1875 [================>.............] - ETA: 1s - loss: 0.2431 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1118/1875 [================>.............] - ETA: 1s - loss: 0.2440 - accuracy: 0.9104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1144/1875 [=================>............] - ETA: 1s - loss: 0.2449 - accuracy: 0.9099"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1169/1875 [=================>............] - ETA: 1s - loss: 0.2459 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1194/1875 [==================>...........] - ETA: 1s - loss: 0.2457 - accuracy: 0.9095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1218/1875 [==================>...........] - ETA: 1s - loss: 0.2457 - accuracy: 0.9093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1242/1875 [==================>...........] - ETA: 1s - loss: 0.2463 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1875 [===================>..........] - ETA: 1s - loss: 0.2465 - accuracy: 0.9091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1875 [===================>..........] - ETA: 1s - loss: 0.2461 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1315/1875 [====================>.........] - ETA: 1s - loss: 0.2455 - accuracy: 0.9095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1340/1875 [====================>.........] - ETA: 1s - loss: 0.2461 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1364/1875 [====================>.........] - ETA: 1s - loss: 0.2462 - accuracy: 0.9090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1388/1875 [=====================>........] - ETA: 1s - loss: 0.2457 - accuracy: 0.9093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1412/1875 [=====================>........] - ETA: 0s - loss: 0.2457 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1437/1875 [=====================>........] - ETA: 0s - loss: 0.2464 - accuracy: 0.9090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1462/1875 [======================>.......] - ETA: 0s - loss: 0.2470 - accuracy: 0.9090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1487/1875 [======================>.......] - ETA: 0s - loss: 0.2473 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1512/1875 [=======================>......] - ETA: 0s - loss: 0.2474 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1537/1875 [=======================>......] - ETA: 0s - loss: 0.2475 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1562/1875 [=======================>......] - ETA: 0s - loss: 0.2478 - accuracy: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1587/1875 [========================>.....] - ETA: 0s - loss: 0.2478 - accuracy: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1612/1875 [========================>.....] - ETA: 0s - loss: 0.2478 - accuracy: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1636/1875 [=========================>....] - ETA: 0s - loss: 0.2478 - accuracy: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1660/1875 [=========================>....] - ETA: 0s - loss: 0.2476 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1683/1875 [=========================>....] - ETA: 0s - loss: 0.2474 - accuracy: 0.9089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1707/1875 [==========================>...] - ETA: 0s - loss: 0.2475 - accuracy: 0.9089"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1731/1875 [==========================>...] - ETA: 0s - loss: 0.2478 - accuracy: 0.9088"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1755/1875 [===========================>..] - ETA: 0s - loss: 0.2478 - accuracy: 0.9087"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1778/1875 [===========================>..] - ETA: 0s - loss: 0.2478 - accuracy: 0.9087"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1802/1875 [===========================>..] - ETA: 0s - loss: 0.2479 - accuracy: 0.9086"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1825/1875 [============================>.] - ETA: 0s - loss: 0.2480 - accuracy: 0.9084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1849/1875 [============================>.] - ETA: 0s - loss: 0.2483 - accuracy: 0.9083"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1874/1875 [============================>.] - ETA: 0s - loss: 0.2488 - accuracy: 0.9080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2489 - accuracy: 0.9079\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1875 [..............................] - ETA: 5s - loss: 0.0746 - accuracy: 0.9688"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  25/1875 [..............................] - ETA: 3s - loss: 0.2727 - accuracy: 0.9050"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  50/1875 [..............................] - ETA: 3s - loss: 0.2665 - accuracy: 0.9031"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  74/1875 [>.............................] - ETA: 3s - loss: 0.2534 - accuracy: 0.9046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  98/1875 [>.............................] - ETA: 3s - loss: 0.2536 - accuracy: 0.9021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1875 [>.............................] - ETA: 3s - loss: 0.2521 - accuracy: 0.9029"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 145/1875 [=>............................] - ETA: 3s - loss: 0.2478 - accuracy: 0.9058"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 169/1875 [=>............................] - ETA: 3s - loss: 0.2442 - accuracy: 0.9070"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 192/1875 [==>...........................] - ETA: 3s - loss: 0.2412 - accuracy: 0.9087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 216/1875 [==>...........................] - ETA: 3s - loss: 0.2414 - accuracy: 0.9091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 239/1875 [==>...........................] - ETA: 3s - loss: 0.2385 - accuracy: 0.9110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 263/1875 [===>..........................] - ETA: 3s - loss: 0.2374 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 287/1875 [===>..........................] - ETA: 3s - loss: 0.2392 - accuracy: 0.9110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 310/1875 [===>..........................] - ETA: 3s - loss: 0.2423 - accuracy: 0.9105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 333/1875 [====>.........................] - ETA: 3s - loss: 0.2432 - accuracy: 0.9102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 357/1875 [====>.........................] - ETA: 3s - loss: 0.2428 - 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\b\b\r",
      " 381/1875 [=====>........................] - ETA: 3s - loss: 0.2409 - accuracy: 0.9101"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 404/1875 [=====>........................] - ETA: 3s - loss: 0.2388 - accuracy: 0.9101"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 428/1875 [=====>........................] - ETA: 3s - loss: 0.2362 - accuracy: 0.9108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 452/1875 [======>.......................] - ETA: 3s - loss: 0.2367 - accuracy: 0.9113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 475/1875 [======>.......................] - ETA: 3s - loss: 0.2365 - accuracy: 0.9112"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 498/1875 [======>.......................] - ETA: 2s - loss: 0.2363 - accuracy: 0.9113"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 522/1875 [=======>......................] - ETA: 2s - loss: 0.2356 - accuracy: 0.9118"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 546/1875 [=======>......................] - ETA: 2s - loss: 0.2362 - accuracy: 0.9115"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 570/1875 [========>.....................] - ETA: 2s - loss: 0.2350 - accuracy: 0.9123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 593/1875 [========>.....................] - ETA: 2s - loss: 0.2352 - accuracy: 0.9122"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 616/1875 [========>.....................] - ETA: 2s - loss: 0.2365 - accuracy: 0.9119"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 639/1875 [=========>....................] - ETA: 2s - loss: 0.2373 - accuracy: 0.9111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 662/1875 [=========>....................] - ETA: 2s - loss: 0.2395 - accuracy: 0.9103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 685/1875 [=========>....................] - ETA: 2s - loss: 0.2400 - accuracy: 0.9102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 708/1875 [==========>...................] - ETA: 2s - loss: 0.2403 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 732/1875 [==========>...................] - ETA: 2s - loss: 0.2401 - 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\b\b\r",
      " 755/1875 [===========>..................] - ETA: 2s - loss: 0.2404 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 778/1875 [===========>..................] - ETA: 2s - loss: 0.2411 - accuracy: 0.9091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 802/1875 [===========>..................] - ETA: 2s - loss: 0.2417 - accuracy: 0.9088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 824/1875 [============>.................] - ETA: 2s - loss: 0.2419 - accuracy: 0.9087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 848/1875 [============>.................] - ETA: 2s - loss: 0.2411 - accuracy: 0.9085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 872/1875 [============>.................] - ETA: 2s - loss: 0.2391 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 896/1875 [=============>................] - ETA: 2s - loss: 0.2386 - accuracy: 0.9095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 919/1875 [=============>................] - ETA: 2s - loss: 0.2391 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 943/1875 [==============>...............] - ETA: 2s - loss: 0.2393 - accuracy: 0.9093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 967/1875 [==============>...............] - ETA: 1s - loss: 0.2394 - accuracy: 0.9090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 991/1875 [==============>...............] - ETA: 1s - loss: 0.2392 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1015/1875 [===============>..............] - ETA: 1s - loss: 0.2397 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1039/1875 [===============>..............] - ETA: 1s - loss: 0.2397 - accuracy: 0.9090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1063/1875 [================>.............] - ETA: 1s - loss: 0.2391 - accuracy: 0.9092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1087/1875 [================>.............] - ETA: 1s - loss: 0.2384 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1110/1875 [================>.............] - ETA: 1s - loss: 0.2391 - accuracy: 0.9093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1134/1875 [=================>............] - ETA: 1s - loss: 0.2394 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1157/1875 [=================>............] - ETA: 1s - loss: 0.2384 - 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\b\b\r",
      "1180/1875 [=================>............] - ETA: 1s - loss: 0.2387 - 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\b\b\r",
      "1203/1875 [==================>...........] - ETA: 1s - loss: 0.2392 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1226/1875 [==================>...........] - ETA: 1s - loss: 0.2393 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1249/1875 [==================>...........] - ETA: 1s - loss: 0.2391 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1273/1875 [===================>..........] - ETA: 1s - loss: 0.2391 - accuracy: 0.9095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1296/1875 [===================>..........] - ETA: 1s - loss: 0.2388 - 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\b\b\r",
      "1320/1875 [====================>.........] - ETA: 1s - loss: 0.2379 - accuracy: 0.9101"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1344/1875 [====================>.........] - ETA: 1s - loss: 0.2380 - accuracy: 0.9101"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1368/1875 [====================>.........] - ETA: 1s - loss: 0.2378 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1392/1875 [=====================>........] - ETA: 1s - loss: 0.2377 - accuracy: 0.9101"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1416/1875 [=====================>........] - ETA: 0s - loss: 0.2381 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1440/1875 [======================>.......] - ETA: 0s - loss: 0.2381 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1464/1875 [======================>.......] - ETA: 0s - loss: 0.2381 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1875 [======================>.......] - ETA: 0s - loss: 0.2392 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1512/1875 [=======================>......] - ETA: 0s - loss: 0.2396 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1536/1875 [=======================>......] - ETA: 0s - loss: 0.2396 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1559/1875 [=======================>......] - ETA: 0s - loss: 0.2400 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1583/1875 [========================>.....] - ETA: 0s - loss: 0.2397 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1607/1875 [========================>.....] - ETA: 0s - loss: 0.2396 - 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\b\b\r",
      "1631/1875 [=========================>....] - ETA: 0s - loss: 0.2395 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1655/1875 [=========================>....] - ETA: 0s - loss: 0.2396 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1678/1875 [=========================>....] - ETA: 0s - loss: 0.2396 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1702/1875 [==========================>...] - ETA: 0s - loss: 0.2394 - accuracy: 0.9100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1727/1875 [==========================>...] - ETA: 0s - loss: 0.2394 - accuracy: 0.9099"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1750/1875 [===========================>..] - ETA: 0s - loss: 0.2394 - accuracy: 0.9099"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1774/1875 [===========================>..] - ETA: 0s - loss: 0.2395 - 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\b\b\r",
      "1797/1875 [===========================>..] - ETA: 0s - loss: 0.2395 - accuracy: 0.9097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1822/1875 [============================>.] - ETA: 0s - loss: 0.2401 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1846/1875 [============================>.] - ETA: 0s - loss: 0.2408 - accuracy: 0.9094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1871/1875 [============================>.] - ETA: 0s - loss: 0.2407 - accuracy: 0.9096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2407 - accuracy: 0.9096\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f659e338ee0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(train_images, train_labels, epochs=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "W3ZVOhugCaXA"
   },
   "source": [
    "モデルのトレーニングの進行とともに、損失値と正解率が表示されます。このモデルの場合、トレーニング用データでは 0.91 (すなわち 91%) の正解率に達します。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wCpr6DGyE28h"
   },
   "source": [
    "### 正解率を評価する\n",
    "\n",
    "次に、モデルがテストデータセットでどのように機能するかを比較します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:10.435844Z",
     "iopub.status.busy": "2022-12-15T00:32:10.435159Z",
     "iopub.status.idle": "2022-12-15T00:32:11.203655Z",
     "shell.execute_reply": "2022-12-15T00:32:11.202902Z"
    },
    "id": "VflXLEeECaXC"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "313/313 - 1s - loss: 0.3393 - accuracy: 0.8804 - 635ms/epoch - 2ms/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Test accuracy: 0.8804000020027161\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_acc = model.evaluate(test_images,  test_labels, verbose=2)\n",
    "\n",
    "print('\\nTest accuracy:', test_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yWfgsmVXCaXG"
   },
   "source": [
    "ご覧の通り、テスト用データセットでの正解率は、トレーニング用データセットでの正解率よりも少し低くなります。このトレーニング時の正解率とテスト時の正解率の差は、**過適合**の一例です。過適合とは、新しいデータに対する機械学習モデルの性能が、トレーニング時と比較して低下する現象です。過適合モデルは、トレーニングデータセットのノイズと詳細を「記憶」するため、新しいデータでのモデルのパフォーマンスに悪影響を及ぼします。詳細については、以下を参照してください。\n",
    "\n",
    "- [過学習のデモ](https://www.tensorflow.org/tutorials/keras/overfit_and_underfit#demonstrate_overfitting)\n",
    "- [過学習を防止するためのストラテジー](https://www.tensorflow.org/tutorials/keras/overfit_and_underfit#strategies_to_prevent_overfitting)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v-PyD1SYE28q"
   },
   "source": [
    "### 予測する\n",
    "\n",
    "トレーニングされたモデルを使用して、いくつかの画像に関する予測を行うことができます。ソフトマックスレイヤーをアタッチして、モデルの線形出力である[ロジット](https://developers.google.com/machine-learning/glossary#logits)を解釈しやすい確率に変換します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.207679Z",
     "iopub.status.busy": "2022-12-15T00:32:11.206990Z",
     "iopub.status.idle": "2022-12-15T00:32:11.227790Z",
     "shell.execute_reply": "2022-12-15T00:32:11.227091Z"
    },
    "id": "DnfNA0CrQLSD"
   },
   "outputs": [],
   "source": [
    "probability_model = tf.keras.Sequential([model, \n",
    "                                         tf.keras.layers.Softmax()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.231616Z",
     "iopub.status.busy": "2022-12-15T00:32:11.231131Z",
     "iopub.status.idle": "2022-12-15T00:32:11.949505Z",
     "shell.execute_reply": "2022-12-15T00:32:11.948638Z"
    },
    "id": "Gl91RPhdCaXI"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/313 [..............................] - ETA: 24s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 46/313 [===>..........................] - 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\r",
      " 93/313 [=======>......................] - 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\r",
      "140/313 [============>.................] - 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\r",
      "186/313 [================>.............] - 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\r",
      "232/313 [=====================>........] - 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\r",
      "275/313 [=========================>....] - 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\r",
      "313/313 [==============================] - 0s 1ms/step\n"
     ]
    }
   ],
   "source": [
    "predictions = probability_model.predict(test_images)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "x9Kk1voUCaXJ"
   },
   "source": [
    "これは、モデルがテスト用データセットの画像のひとつひとつを分類予測した結果です。最初の予測を見てみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.954194Z",
     "iopub.status.busy": "2022-12-15T00:32:11.953539Z",
     "iopub.status.idle": "2022-12-15T00:32:11.958897Z",
     "shell.execute_reply": "2022-12-15T00:32:11.958219Z"
    },
    "id": "3DmJEUinCaXK"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5.6910987e-09, 2.4519869e-07, 5.8553162e-08, 3.0318517e-08,\n",
       "       3.1033121e-08, 3.6219638e-04, 2.5309854e-08, 1.5150005e-02,\n",
       "       8.6693162e-06, 9.8447871e-01], dtype=float32)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-hw1hgeSCaXN"
   },
   "source": [
    "予測結果は、10個の数字の配列です。これは、その画像が10の衣料品の種類のそれぞれに該当するかの「確信度」を表しています。どのラベルが一番確信度が高いかを見てみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.963143Z",
     "iopub.status.busy": "2022-12-15T00:32:11.962410Z",
     "iopub.status.idle": "2022-12-15T00:32:11.967388Z",
     "shell.execute_reply": "2022-12-15T00:32:11.966730Z"
    },
    "id": "qsqenuPnCaXO"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(predictions[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E51yS7iCCaXO"
   },
   "source": [
    "このモデルは、この画像が、アンクルブーツ、`class_names[9]`である可能性が最も高いと判断したことになります。これが正しいかどうか、テスト用ラベルを見てみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.971252Z",
     "iopub.status.busy": "2022-12-15T00:32:11.970734Z",
     "iopub.status.idle": "2022-12-15T00:32:11.975399Z",
     "shell.execute_reply": "2022-12-15T00:32:11.974767Z"
    },
    "id": "Sd7Pgsu6CaXP"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_labels[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ygh2yYC972ne"
   },
   "source": [
    "これをグラフ化して、10 クラスの予測の完全なセットを確認します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.979007Z",
     "iopub.status.busy": "2022-12-15T00:32:11.978512Z",
     "iopub.status.idle": "2022-12-15T00:32:11.985062Z",
     "shell.execute_reply": "2022-12-15T00:32:11.984393Z"
    },
    "id": "DvYmmrpIy6Y1"
   },
   "outputs": [],
   "source": [
    "def plot_image(i, predictions_array, true_label, img):\n",
    "  true_label, img = true_label[i], img[i]\n",
    "  plt.grid(False)\n",
    "  plt.xticks([])\n",
    "  plt.yticks([])\n",
    "\n",
    "  plt.imshow(img, cmap=plt.cm.binary)\n",
    "\n",
    "  predicted_label = np.argmax(predictions_array)\n",
    "  if predicted_label == true_label:\n",
    "    color = 'blue'\n",
    "  else:\n",
    "    color = 'red'\n",
    "\n",
    "  plt.xlabel(\"{} {:2.0f}% ({})\".format(class_names[predicted_label],\n",
    "                                100*np.max(predictions_array),\n",
    "                                class_names[true_label]),\n",
    "                                color=color)\n",
    "\n",
    "def plot_value_array(i, predictions_array, true_label):\n",
    "  true_label = true_label[i]\n",
    "  plt.grid(False)\n",
    "  plt.xticks(range(10))\n",
    "  plt.yticks([])\n",
    "  thisplot = plt.bar(range(10), predictions_array, color=\"#777777\")\n",
    "  plt.ylim([0, 1])\n",
    "  predicted_label = np.argmax(predictions_array)\n",
    "\n",
    "  thisplot[predicted_label].set_color('red')\n",
    "  thisplot[true_label].set_color('blue')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zh9yABaME29S"
   },
   "source": [
    "### 予測を検証する\n",
    "\n",
    "トレーニングされたモデルを使用して、いくつかの画像に関する予測を行うことができます。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d4Ov9OFDMmOD"
   },
   "source": [
    "0 番目の画像、予測、および予測配列を見てみましょう。 正しい予測ラベルは青で、間違った予測ラベルは赤です。 数値は、予測されたラベルのパーセンテージ (/100) を示します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:11.988857Z",
     "iopub.status.busy": "2022-12-15T00:32:11.988220Z",
     "iopub.status.idle": "2022-12-15T00:32:12.107037Z",
     "shell.execute_reply": "2022-12-15T00:32:12.106256Z"
    },
    "id": "HV5jw-5HwSmO"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 0\n",
    "plt.figure(figsize=(6,3))\n",
    "plt.subplot(1,2,1)\n",
    "plot_image(i, predictions[i], test_labels, test_images)\n",
    "plt.subplot(1,2,2)\n",
    "plot_value_array(i, predictions[i],  test_labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:12.110865Z",
     "iopub.status.busy": "2022-12-15T00:32:12.110236Z",
     "iopub.status.idle": "2022-12-15T00:32:12.234702Z",
     "shell.execute_reply": "2022-12-15T00:32:12.233933Z"
    },
    "id": "Ko-uzOufSCSe"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 12\n",
    "plt.figure(figsize=(6,3))\n",
    "plt.subplot(1,2,1)\n",
    "plot_image(i, predictions[i], test_labels, test_images)\n",
    "plt.subplot(1,2,2)\n",
    "plot_value_array(i, predictions[i],  test_labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kgdvGD52CaXR"
   },
   "source": [
    "いくつかの画像をそれらの予測とともにプロットしてみましょう。確信度が高い場合でも、モデルが間違っていることがあることに注意してください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:12.238326Z",
     "iopub.status.busy": "2022-12-15T00:32:12.237801Z",
     "iopub.status.idle": "2022-12-15T00:32:14.072215Z",
     "shell.execute_reply": "2022-12-15T00:32:14.071474Z"
    },
    "id": "hQlnbqaw2Qu_"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1000 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the first X test images, their predicted labels, and the true labels.\n",
    "# Color correct predictions in blue and incorrect predictions in red.\n",
    "num_rows = 5\n",
    "num_cols = 3\n",
    "num_images = num_rows*num_cols\n",
    "plt.figure(figsize=(2*2*num_cols, 2*num_rows))\n",
    "for i in range(num_images):\n",
    "  plt.subplot(num_rows, 2*num_cols, 2*i+1)\n",
    "  plot_image(i, predictions[i], test_labels, test_images)\n",
    "  plt.subplot(num_rows, 2*num_cols, 2*i+2)\n",
    "  plot_value_array(i, predictions[i], test_labels)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R32zteKHCaXT"
   },
   "source": [
    "## トレーニングされたモデルを使用する\n",
    "\n",
    "最後に、トレーニング済みモデルを使って 1 つの画像に対する予測を行います。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:14.076834Z",
     "iopub.status.busy": "2022-12-15T00:32:14.076304Z",
     "iopub.status.idle": "2022-12-15T00:32:14.080347Z",
     "shell.execute_reply": "2022-12-15T00:32:14.079668Z"
    },
    "id": "yRJ7JU7JCaXT"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(28, 28)\n"
     ]
    }
   ],
   "source": [
    "# Grab an image from the test dataset.\n",
    "img = test_images[1]\n",
    "\n",
    "print(img.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vz3bVp21CaXV"
   },
   "source": [
    "`tf.keras` モデルは、サンプルの中のバッチあるいは「集まり」についてまとめて予測を行うように最適化されています。そのため、1 つの画像を使う場合でも、リスト化する必要があります。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:14.083905Z",
     "iopub.status.busy": "2022-12-15T00:32:14.083384Z",
     "iopub.status.idle": "2022-12-15T00:32:14.087360Z",
     "shell.execute_reply": "2022-12-15T00:32:14.086713Z"
    },
    "id": "lDFh5yF_CaXW"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 28, 28)\n"
     ]
    }
   ],
   "source": [
    "# Add the image to a batch where it's the only member.\n",
    "img = (np.expand_dims(img,0))\n",
    "\n",
    "print(img.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EQ5wLTkcCaXY"
   },
   "source": [
    "そして、予測を行います。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:14.090941Z",
     "iopub.status.busy": "2022-12-15T00:32:14.090364Z",
     "iopub.status.idle": "2022-12-15T00:32:14.157532Z",
     "shell.execute_reply": "2022-12-15T00:32:14.156755Z"
    },
    "id": "o_rzNSdrCaXY"
   },
   "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 24ms/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[2.4473981e-04 1.2069421e-11 9.9653888e-01 2.1565708e-14 1.3155717e-03\n",
      "  2.2960410e-12 1.9008714e-03 8.9515721e-13 2.3349067e-10 3.9004930e-16]]\n"
     ]
    }
   ],
   "source": [
    "predictions_single = probability_model.predict(img)\n",
    "\n",
    "print(predictions_single)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:14.161153Z",
     "iopub.status.busy": "2022-12-15T00:32:14.160625Z",
     "iopub.status.idle": "2022-12-15T00:32:14.254094Z",
     "shell.execute_reply": "2022-12-15T00:32:14.253343Z"
    },
    "id": "6Ai-cpLjO-3A"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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hQwft3r3ba/8+AeEPvPbaa3K5XAoNDdWxY8c83ps9e7aSJUumQ4cOea0e95d3//79+uGHHzyGvcePH6+sWbPq1Vdf1dGjR71W0/9qw4YNypkzp+rVq6ctW7Y4r/v6hHbr1i116dJFvXv3liRdunRJmzdvVmRkpF5//XX99NNPPq3v98yZM0fBwcHq3LmzR507duzwYVV/zP0737Nnj7755hstX77c4/23337bpyHBXd8vv/yiwMBAvffee5KkzZs3q1mzZipfvrzmz5/vfH7FihU6c+aMT2r9q9z/bfcGm9GjR8vlcmn48OG6fPmy1+v65ZdfFBYWpsWLFzuvbd++XR06dFCuXLk0Z84cr9eUUNy/g6NHj2rv3r06ePCg897UqVNVtGhRderUyQkJb775psd2edgICPE8KPGPGzdOLpdLb7zxhs6dO+e8vmnTJoWFhennn3/2Sn3unWfhwoUKCwtTWFiYChQooGLFiun48eNOrdmyZdNrr73mdyMJ7vp37typJUuWaNasWTp79qwkad26dQoNDVXLli21bds2X5bpoUWLFipatKgOHz6s1q1bq2rVqipbtqwef/xxNW7c2Ke1ubfn5s2bNXPmTL3//vs6evSosx/PmTPHGUlYv3693njjDblcLl24cMHn4et+3DUtWrRIISEhKliwoNKkSaNGjRp5jIS8/fbbCggI0OjRo31S5/r16zV9+nQNGDDA4/UtW7bo2WefVfny5TVmzBgNGTJELpdLJ06c8Emdf4V7269Zs0Y9evTQiy++qEGDBjnvjxo1Si6XSyNGjPB6SDh+/LiCgoL0ySefeLz+448/KmfOnMqSJYs+/fRTr9aUEOIf3/Pnz68sWbIoT548atCggW7duiUpLiSUKlVKlStX1rPPPiuXy6WtW7cmWE0EhP8vfjg4dOiQdu/e7REG3AfX3r17KyoqSrt371atWrVUsmRJrw4lrlu3ToGBgZo6dapu3rypdevWyeVyafLkyc5nxo8fr5QpU+rNN9/UnTt3vFbbn7FgwQLlyJFDxYoVU5kyZRQYGKjVq1dLkqKiohQaGqrWrVvrhx9+8Hpt7i/oli1bnJGZ7777TkWLFlVAQICaNm2qRYsWSYo7iRUpUkQXLlzwep3xa124cKEyZMigqlWrKnPmzKpevbo+/vhj55bDZ599pvz586tQoUIKCQnxyXb9I/HDysqVK5U+fXpNnTpVUtzoksvlUt26dbVr1y7nc4MGDdJjjz2mixcvJmhtkZGRGjlypPPny5cvq1atWnK5XGrUqJEkeXzHfvzxR3Xs2FFhYWEqWLCgx4iYv1u0aJECAwPVtWtX9enTR3ny5FGRIkV0+/ZtSXEjCSlSpNCQIUN05cqVBKnBvS/E///nzp3TM888o969e3sckyWpadOmqlixokqWLKlVq1YlSE3etHbtWqVKlUqTJk3S6tWrtWDBAuXKlUtPP/20852eN2+eevToocaNG3t8JxICAUGeB6gBAwaocOHCSpkypcqVK6eXXnrJeW/YsGFyuVxyuVx64YUX1LhxY+fL462QMHr0aKemQ4cOKUeOHOrSpYv1uYkTJ2r//v1eqenP2rRpk4KCgpyD/549e+RyufT222872y8qKkpp06ZVhw4ddPPmTa/VFv+EGxISoldeeUUnT57UnTt3FB0dbZ1Yu3fvrtq1ays6OtprNd4rKipKmTNn1rRp0yRJu3btUrJkyVSqVClNnjzZ2aa7du3S999/74wy+YtFixZp7969kuK2/5UrV9S9e3cNGTJEUtz+nStXLrVq1UpZs2ZVlSpVtGPHDud3de/J4mG7e/eupk2bZo1offvtt4qIiFDatGmd75j7OCDF3Yr69ddfndGxxODkyZMqVKiQxo8fL0k6fPiwnnjiCbVv397jc0OHDlVQUFCCbPv4x9D421OS3n33XaVPn17jxo1ztuuVK1fUpEkTTZw4UeXKldOrr7760GvytqFDh1ojkwcPHlTOnDnVtGlTj9fv3UYJgYAQz4gRI5QhQwZ98cUXWrt2rd58800VKlTI4xf2/vvvy+Vyafz48bp06ZKk/04Q84bnnntObdu21fnz5xUSEqKOHTs6B8zp06dr1KhRXqvlr5o1a5ZatmwpKe7g7x7+drt69aqkuCHcAwcOeL2+//u//1OqVKk0ZcqUB05I3LJli3r37q306dP79H7+nTt3NHz4cEVGRkqKO4i4T6a1atVSrly5NG3aNK/um3/Fzp07FR4erkaNGjkn2Vu3bmnx4sXav3+/Lly4oOLFi6tdu3aSpC+++EIul0vly5fXnj17vF7vV199pcGDBzt/3rx5s6pUqaKQkBD98ssvkuR3o3V/xd69e5U3b17dvn1bJ06cUHBwsDp16uS8/8UXXzj/+/z58w/9348fDiZOnKhmzZqpefPmztI+SXr99deVKVMm1a9fXx07dlSZMmVUrFgxSXHHxWrVqvnlrbO/4oUXXlCJEiWcP7v3qY8//lgFCxb0esj/RweE+DvT5cuXVbduXb377rvOa9HR0Zo7d64KFCig//znP87rb731llwul8aOHZugQ5zxr5SuX78uKe6qq2bNmnr88cfVoUMHSXFfrpiYGHXt2lUvvfSS81lfu/fLOnToUFWtWlVHjx5V9uzZ1bFjR+fAsGjRIkVGRvqs9ps3b6p169bq27evpLj9Ydu2bRowYICGDh2q8+fPa+fOnerWrZuKFi3qF5P99u3bp7179+ratWsqV66cXnzxRUnSkSNHlD59ehUsWNAZXfBHH330kSpXrqwmTZo4IwnuUaP58+erVKlSzgTgJUuWqHbt2sqfP7/X59bExsZq4sSJcrlcevPNN53XN2/erJo1aypnzpxOnf4ayB5k9+7diomJ0enTp1WpUiUtXLhQ2bNnV6dOnZyT0/79+/Xcc8/pm2++kZSwk4fdqxVeffVVvfLKKwoNDVXbtm2d92fOnKmePXuqRo0a6tKli7O/NG7cWJGRkYl25Yjbl19+qdy5c2vu3Lkery9ZskShoaE6efKkV+v5xwaEe3ek2NhYFStWzOOWghQ3jBMREaEWLVp4vD5ixAi5XC5NnDgxQb4w7r9z2bJlqlGjhlatWqWYmBj9/PPPKl++vHLnzq0VK1ZIihvSHDhwoJ544gmPyVz+4Ntvv3WuAr777jtVrlxZGTJkcL707t9DZGSkWrZsmWD3Nv+Mli1bqkKFCvrll1/Utm1bVa1aVSVKlNDjjz/ujHzs3r3bJ7PS77ePuQ/g69evV6FChZwr682bN6tatWpq3bq1X65miX+l/cEHH6hOnTpq2rSpx4ztkSNHKnfu3M62HjBggN555x2fXaVfv35dU6ZMUZIkSZxbIJL0ww8/qE6dOkqbNq3fTQq+173bbteuXQoODtaxY8d08eJFVa5cWUmSJFGrVq08PvfKK6/o6aefTvD9fvbs2XryySf1/fffS4oLialTp3YmqrrFP3afPXtWAwcOVIYMGZyQmRi4v88nT57UwYMHnblMv/76qxo1aqS6des6qzNu376t/v37q1SpUl6f8/SPDAibN2921vT27dvX6TjXrVs31axZ09rRBg8erOrVq+vmzZseO+eYMWMSdKd0Txp64403nGFMSdq6dauKFi2qQoUKKSwsTNWrV1fWrFn9ava/FDdkHBkZqapVq0qKu2fovp88bdo03blzR6dPn9aAAQOUMWNGrw4d3++Eu3TpUpUsWVJJkyZV06ZNtWDBAklxt25Klizps/kG7lq//fZbjRgxQv3799fXX3/tXD2tWrVKoaGhWrp0qWJiYjR48GC1a9fOuWXjb+6dMV+oUCElTZpUzZo1c2437N+/X2nTptVTTz2lihUrKl26dNq+fbtX6nOPApw4ccLqIzFhwgQrJHz33XeKiIjwyW2xP2vUqFFq0qSJxz68ceNGhYWFOfey9+zZo4wZM6pu3br65JNPtHLlSr388stKly5dgoyY3bp1y6OeSZMm6fXXX5cUd2EUFBSksWPHaurUqUqaNKlzu8nt/Pnzatu2rXLlyqUff/zxodeXUOKv1smbN69CQ0OVLl06devWTYcOHdLhw4fVpEkT5ciRQ/ny5VOVKlUUFBTkk+P7Py4gnD17Vi6XS926dVOnTp2UJk0aZybo9u3blTlzZrVu3dpZOnL16lVVrlzZGc6XvDMh8fDhw8qdO7fef/9959+8ffu2Nm3apBs3buj8+fNatmyZ+vbtqzlz5ni1F8NfsWXLFgUEBDhp+OLFi6pbt64KFy6s9OnTq3z58goNDfXqzh//hDtkyBD179/fWUJ19epVfffddx6f79Kli+rXr+/TRkkLFixQYGCgKlWqpNKlS8vlcumVV17R8ePHdf78eadxTIECBXx2MPkrVq5cKZfLpTFjxujzzz9Xv379VLhwYTVp0sQ5Ke/atUsdOnRQnz59Ejw8Tpw4UWvWrHGusufPn6+QkBBnueWaNWucE6k7JMS/3eDPTbSkuPk1AQEBHsFx+fLlCg8Pl/TfY9rWrVtVtWpV5ciRQ/nz53cmhj5sCxYsUOPGjVW0aFG98cYbzuuHDh3SuXPnVKxYMQ0fPlySdODAAWXLlk0ul0v9+vXz+HuOHj1q9adJDKKiopQqVSqNGTNGW7du1XvvvacyZcqoUaNGOnz4sM6dO6f169frlVde0XvvveezCef/qICwbt06HT58WFu3blVAQIBSpUqlNWvWSPrvVcP333+v0NBQFStWTIUKFVLp0qVVqFAh5+CQ0JNg3H//Tz/9pOLFi2vr1q06d+6cRo0apUqVKildunSqWLGiNmzYkKB1/B3xt01MTIzz5169eqlatWrOFzk6OlpbtmzR5MmTtXbtWp/Mrl+4cKHSpUunli1b6sUXX1RQUJB1G2n37t3q1auX0qdPr507d3q9RrcDBw4oe/bsmjp1qrNN58yZo4wZMzpNnI4ePaopU6Zo3Lhxfrd6Jb7Y2FjFxMSoffv2at68ucd7H3zwgfLnz69mzZo5V+N3795N0O+c++/Oly+fsmfPru+++047d+5UaGioRo0apbVr16pmzZrKnj275s+f76xHnzx5stMXILFYu3atAgMD1bZtW8XExGjJkiUqUqSIJM/v7s2bN3XmzBmdPXs2QUahJk+erLRp06pnz56KjIxU0qRJNWHCBOf9TZs2KXv27M5+fODAAbVs2VKrVq3ymOORGCckumvu3bu3x20T6b8jmO55UP7gHxMQrly5onbt2qlv377auHGjUqZMqSRJkqhnz546deqUpP/+8g4cOKA5c+aoX79+ev/9952rCm/c/3Tfgz969KgyZMigmjVrKnPmzGrYsKHeeecdrVixQvnz5/ebdrP3WrVqlRYvXuwxeXPp0qXKkyePM8nJ19wz/t2jMwcOHFCGDBnUsWNH5zObNm1S586dFR4e7rWhbbezZ89q8+bNzijWrl27lCtXLm3fvt3joDhr1iwlSZJE69ev92p9D0PXrl1VvXp1a6lWZGSkUqZMqZo1ayZ4A7J7RwIrVaqksLAwzZgxQ3369PF4LyIiwgoJ06ZNS1T3vSVp9erVCgwMVPfu3fXZZ5+pTJkyWrlypaKiorRnzx5t3bpVy5Yt0+nTpxPk3586daqSJ0/u0f2vRYsWGj9+vDPH4eDBg8qdO7e6deumvXv3qmbNmmrUqJGz7ye2iaD306tXL1WvXl1379712A9HjhypjBkz+s3twX9MQJDiDqg5cuRw5h+sWrVKSZIkUdeuXf/wC+GNnXL79u0KCAjQxo0bJcW1xe3fv79Gjx7tMUGoevXqGjduXILX81ddv35d3bp1k8vlUsOGDZ0hQklq3bq1x/IdX9q2bZueeuopSXFBzN2S2G3z5s2S4m6PuMOjt+zZs0flypVTrVq11LhxY929e1ebN29W8uTJnclb8ftDFCpUyGOFTWIxatSo+95a+uSTT1S4cGG1aNEiQUeW3Aflw4cP67333nPm+JQqVUoul0s1a9a0wktERIRy586tmTNnemUN+sNy75X2119/rX/9619KnTq1cufOrdDQUGXJkkX58uVTcHCwsmbNmiC3LNeuXSuXy6WhQ4d6vB4eHq6nnnpKadKkUbly5TR+/HiNHj1awcHBypEjh0qXLu21EVxvGTNmjAIDA52Wye7/rpUrV6pAgQJ+81Tef0RAiL9TPffcc2rSpInTLvTzzz9XkiRJ1L17d6clapMmTTweuuItR44cUb169ZQ2bVpt2rRJkufJ4O7duxowYIAyZ87sMWnR33z33Xd69dVXlTlzZpUqVUrjx4/XokWLVL16dX3++eder8f9+1+7dq2+/vpr7d27V2XLltWqVausJV07duzQc88955PnLOzevVvp06d3nqUR/8qiadOmKlCggMdM/1u3bql48eL64IMPvF7rn+Xe9vv27dOOHTs8btWULFlSBQsW1ObNm53Jan379tWAAQMSZK29m3u77ty5U08++aQaNWrkcUX7zDPPKCgoSKtXr7YuDJ555hkVLlzYp6tt/iz3tr9y5YquXbvm8d66dev0+OOPq06dOjp27JjOnz+vy5cv69y5c05/l4dt//79qlChgho0aOCE8MaNGytPnjyaN2+eli9froIFC6pEiRLasWOHTp48qY0bNzq/r8TYZ8Jd88GDB7Vv3z6P44p7ieyOHTuc/T8yMlLFihVLsN/BX/VIB4T7TSZcu3atGjVq5FylS3FNQAICAlSjRg0VK1ZMTz75pFeuEOIHl/gP6WjWrJlSpUrltGmNiYnRRx99pIYNGypbtmx+MwHNXfOOHTu0ePFizZ8/36N73NmzZ9WhQwdVq1ZNqVKlclpVe+sqIP6/s3btWqVOnVqLFi3SwYMHVaJECaVMmVIvvPCCx8/06tVLVapU8fqT686fP6/y5cure/fuHq+79+Fvv/1WtWrVUr58+bR69WqtW7dOAwcOVMaMGT1Cgz+aP3++MmXKpJCQEOXOndtZ9nrjxg2VKlVKoaGhKlmypGrUqKEUKVJ4ZTXLvn37FBQUpP79+993bXm5cuWUM2dOffPNN9ZxxN86Ut6Pe9//8ssvVblyZRUrVkwVK1bU7t27nVska9asUerUqdW5c2ev9R/Zv3+/atWqpbp166pcuXIqVqyYx/LQrVu3yuVyaenSpR4/l5j6G8yYMcPpFivFPfUzJCREmTJlUp48edSsWTPdvn1bZ8+eVa1atZQmTRqVLFlSVatWVbp06fxqRcYjGxDiD5G9++67zsz0O3fuqH79+oqIiPD4fFRUlHr27Kk+ffp4dc7BunXrnFrdX+ojR46oWbNmSp06tbOz7Nq1Sz179vTag6H+LPfBP2/evMqePbsee+wxff75586s7tjYWJ08eVIjR45UeHh4gvcOv58TJ05o1KhRGjZsmPPaV199pWTJkqljx45asWKFtmzZosjISJ9NSNyzZ49y586tdevWPfBg+MMPP6hVq1YKCAhQnjx5VLBgQb8Ji/dy78vnz59XWFiYPv74Y61Zs0bvvPOOkidP7vEgoIkTJ2rgwIHq06ePV+7p37hxQ02bNlXXrl09Xr99+7YOHTrkhNxatWope/bs2rBhQ6I6QbktXbpUadKk0cCBA7V69WqVLVtW4eHh+uqrr5yQsHr1arlcLnXt2tVrwX3//v2qXr260qVLp88++0zSfyc1b926VQUKFNC3337rlVoetrNnz6pevXoqXbq05s6dq1OnTik0NFSTJk3SmjVrNHfuXAUHB6tq1arO9p46daqGDRumYcOG+d0E40cyIGzfvl0ul0tLlixRjx49lCFDBo81yqdPn1ZYWJjT/+B+k1+8EQ4uX76s6tWrK2PGjE6Kjv845yJFiujxxx93huP8bYht27ZtCgoK0scff6wzZ87ozJkzat++vQIDA53H9MY/6Piij8ChQ4fkcrmULl06a8b5vHnzVKxYMT322GMqVKiQSpYs6fUJiW6zZs1SsmTJ7vvIXfd+GR0drX379um3337T0aNHvT7K8Vd9/fXX6t+/v15++WXnhHT16lW9//77Spo0qdU731snqDt37qhChQrOo5qluGWAkZGRSps2rYKDg9WkSRNJcSEhXbp0zvyPxOLQoUMqUaKExowZI0n67bffFBoaqkyZMilTpkz66quvnNuX69at83qDtV9++UU1a9ZU7dq1PSbZ1qtXT5UrV06Ugcxt+/bteu6551SlShX17NlTrVq18hiR3rdvn7JmzarnnnvOh1X+OY9kQJDi2vqmSpVKgYGBHleEd+/e1Z07dzR06FC9/PLLun79uk93xo0bN6p27doKDQ21Jga98MILSpIkibJkyaIbN274tM6VK1daEzkXL16sYsWK6eLFix4H97Zt2ypLlizOSoZ7n9CWkKKjo/Xbb79p7dq1zpyS2bNny+VyqVmzZtYDdM6cOaN9+/bp0KFDCf5kwN+zYcMGpUyZ0mnOdD/jx4/XM88849WHWP1dt27d0sCBA5U0aVIVL17c4z13SEiZMqWzTFPyXkC4fPmywsLC1KFDB/300096++23lS9fPkVERGjcuHH68MMPlSNHDqfPQbVq1fy6CdL9/PzzzxoxYoSuXbumU6dOKU+ePM5zT0qWLKnw8HAtWbLECW6+4L7dUKdOHX3zzTdq3Lixx+3dxB4SWrVqpdDQUD399NPO6+6LvA8//FAFChTQ0aNHvXp8/KseqYAQf4dyP3kxWbJkWrhwofXZDRs2KHPmzM5DSLzxy3H/G7dv3/aYNLRr1y5Vq1ZNoaGhOnLkiPN6ZGSkPvvsM5/OaHW3d3YPQ8Y/wU6dOlWpU6d2dnr3ievAgQMKDg52HpnsLT///LOef/55hYWFKWXKlEqTJo1atGihkydPatGiRU4vfX+ZABTfiRMnlClTJjVo0MBjH4i/X/bu3Vv9+/f3ywOJW/zajhw5oqFDhzotyeO7du2aRo0apccee0y//fab1/+bVq9erWTJkilHjhxKkyaNJk+e7ISA27dvq0aNGlZfjMTG/d/z0ksvKSIiwlk617p1a7lcLj355JPW5EVv279/v+rWravkyZMrX758Tjjwt9HSv2PXrl1q3ry5UqdOrcmTJ3u8t2zZMgUHB/tlK/T4HqmA4DZ06FB17NhRu3fv1tChQ5U8eXLNnDlTkmeImDx5sooUKeKVTlzxJw01atRI4eHhat++vb766itJcU9Tq169uoKCgvTaa6+pdevWypIli887JLqHtxcsWKDkyZOre/fuzpLL3377TQULFrQezezuAhkVFeW1Onfs2KEsWbKoc+fOmj59uvbt26d+/fopNDRU+fLl07Fjx5yRhLfffttZxeJPFi5cqICAALVu3dpjol50dLQGDBigHDly+N0cFDf3/n3vgf3YsWN69dVXFRgYaB0ko6Ojvd5bPr5jx45py5Yt1q2amJgYNW3aVIMGDXIehObP3Nv+4MGD+vnnn63bIXXq1PHoQNizZ0/9+OOPzgibr+3bt0/dunXz6twvb9m7d69atGih0qVLa9KkSZLiwnGfPn0UFhbm97cJH4mAEH/uwMqVK5U3b16nyYwU96CX5MmTO+1+pbgvyYwZMxQREaGVK1d6pc7PP/9cKVKkUI8ePfTGG2+oRIkSKlOmjPMM9lOnTqlHjx4qUaKEnnnmGZ/PZv3oo480c+ZMZ8Lh4sWLnTbVv/76q2JiYjR27FiVKVNGbdu21eXLl3XixAm9/vrrypkzp9cOQDt27FDq1Kk1YMAA6+Ayb948PfXUUypVqpRu3rypyZMnK3ny5Hrttdf8LiTExMRo8uTJSpYsmcLCwtS2bVt16dJFDRo0UKZMmfx+QuLq1avVpk0btWzZ0uOEdPz4cQ0cOFBp0qTxmN3tj27duqVBgwYpa9asfjdh7H7i9/XPnz+/ChUqpMyZM6tly5ZO/Q0bNlT+/Pn10UcfqUuXLkqXLp3fXrk+SuHAbefOnWrRooUCAgJUtGhRtWjRQmFhYc4qNX+WqAPCvcu7Zs+erR49eqhnz56SPHe2V199VS6XS927d1fZsmVVqFAhSXGz8N2TABNKbGysLl++rCpVqnj0HT979qy6du2qp59+2mM4/vLlyz7v7X737l2VLFlSRYoU0cKFC50RAndIeOmll3Tt2jXduHFD7733ngoXLqzkyZOrUKFCypYtm0dAS0jHjh1TxowZ1bRpU+e12NhY64mB//rXv5x+AW+99ZaCgoJ07tw5r9T4V23atElNmjRRkSJFVKFCBfXr189vT1bxT1Bp06ZVhw4d1K9fP+XMmVMNGjRwwvvx48f1+uuvy+Vy6eOPP/ZhxQ/26aefqnv37sqcObPfhrH7WbNmjQIDAzV16lRdu3ZNy5cvl8vl0uzZsyXFjdRUqFBBBQoUUHh4uM8vPB41f2YOwd69e9WqVStlzpxZQ4YM8fuRA7dEGxDatGnjPFHNvUSmXLlycrlcqlat2n1ng48dO1Y1a9ZU69atE/wE7O45L8V1GHSfcN0Tn9zvnTt3ToULF1ZkZGSC1vNXuLfd9evXVatWLRUvXlzz589/YEiIjY3V9evXtWDBAkVFRXl1nfjhw4dVsmRJNWjQwGrlHP8LW7FiRTVs2ND5sy+Htv8Mf20n695v43+vtm/frieffNKZZ3D48GFlyZJFLpdL5cuXd8LakSNHNGzYMJ80ofojP/30kypXrqxGjRoluvbJQ4YMcTqB/vLLL8qTJ49H23C306dP+92oWWLmPr5cvnxZt2/fdppnPSgo/Pjjj+rYsWOi6KPhlmgDwtKlS50JLe574nfu3FHz5s2VNWtWffzxx04IiH8wi98BLaGaIcX/e+fMmaPnn39ehw8fVsWKFdW2bVunJnddkZGRqlatml+dFNwH9evXr6tatWoqUaKE5s+fb91u6Nq1q8/bgrpnQ9esWdMjJMT/olauXFktW7a873v+6H5NtHwtfnviKVOm6IcffpAU11PCPWp37Ngx5cqVSx06dHD6/jds2DBRTD779ddf/XIC6++JjY1V3bp19eqrr+rmzZvKli2bOnbs6Owz48ePd0YS8PC4t+8XX3yh+vXrq0SJEqpfv76WLVv2uz+XGFYgxZfoAsK9B8upU6eqWbNmzpDgnTt3VLduXRUpUkTz5s1zlvHce/JNqIPurl27NGTIEMXExOi3335Trly5nOcmrFixQi6Xy+qd36xZM+cJa/7AvW3cV9nR0dGqVq3afUcSUqRIobZt21rLB70tfkiI32QlJiZGx48fV+3ata2+F/jz7tee2L0CSJLzIKmGDRuqVatWio2N1bVr11SiRAm5XC7VqFHDV6U/8j755BOVL19eGTNmVJcuXTxGT9u1a6euXbsmuhNTYrBs2TKlTJlSI0aM0Pz589W2bVu5XC6vdAL1lkQXEO41adIkPfXUU+rYsaNHSKhdu7aKFi2qzz77zGtfDneDpgkTJmjNmjV688031blzZ4+lRBMmTJDL5VKLFi3Uq1cvderUSYGBgT7pMPh7Nm3apGbNmjkzot0h4d6RhHnz5ilDhgweD5PylQeNJPTr10/h4eGJamjPH/1Re+JLly4pPDzcea7BzZs31b59e3355Zc+X43zKHCf+E+cOKGffvrJ+fO2bdtUsWJFFShQwOkYe+3aNQ0cOFBZs2b125UviZE7KEdHR6t+/foaOXKkJOnkyZPKkSPHfW/tJGaJJiDEv6d/rw8//FDFihVTu3btPEJCvXr1lDVrVq1evTrB69uzZ49SpUqlwYMHS5Jee+01Z63xvY/uXLNmjRo0aKCqVauqcePGPmnt+0dmzpypIkWK6LnnnnMmccYfSVi4cKETEvzl0aSSZ0jYtm2bRowYocDAQJ91SHxU/F574hMnTmj//v2Kjo5W8eLF1bBhQx0+fFivvPKKnnzyyQR7dPA/0YIFCxQSEqKQkBAVLFhQa9eulRS3fLps2bLKlSuXypcvr6pVqypLliyJarKlvxo9erTHHLHY2FhdunRJuXLl0vr163X27Fnn1o7bjBkzHolglmgCQnxffPGFlixZojVr1jivTZ061QkJ7lm6t2/fVu/evRP83v6uXbuUMWNG5c+f33nt7NmzGjlypJIkSeKsf5X+e6vDParh69UK0oOH3OfMmaPy5curefPmzv3m6Oho1axZU7lz53YeqOJvQ/b79+9XvXr1lClTJiVPnjxRLCfyd3/UnjhHjhyqUaOGFi1apNy5cytbtmwKCQnhBPUQuC+M9uzZo1y5cmnUqFFau3atatasqeDgYKf75q5duzRjxgy99NJLmjJlil8/8TWxuHHjht555x0FBgbqtddec16/e/euWrdurWHDhjlPhHUf28+ePavnn39en376qd8dG/8qvw8I3bp182jHGhkZqUyZMumJJ55QoUKFPJ5+N3XqVBUvXlwdO3Z0HpfsllAhYfv27UqdOrUqV66srFmzqlu3bs57Fy9edEYSPvnkE0lxJ1P3/7n/7Av3G43Zt2+fdVCZNWuWKlSooGeffdYJXteuXVPDhg39etj4p59+UoMGDZznreN/82faE+fPn1+RkZH69ddf9e233zJy8Dfdb6XIxo0bNWPGDPXp08fjsxEREU5I8GXb5EfZhQsXNH78eKVPn14DBw50Xu/fv79cLpdq167t8TTM/v37K1++fB4dURMrvw4IFy5cUM+ePVWgQAG9+eabOnbsmMqWLasdO3Zo7969GjNmjPLmzat27do5P/Phhx8qJCTEeaRsQp6AN2/erOTJk2vIkCG6e/eupkyZoowZM3qEhEuXLmnQoEFyuVxON0dfcx94Tpw4oblz52rWrFlasGCBqlWrpk6dOln9JWbMmKGgoCC1aNEiUT20xhuP7P4n+b32xLdu3dIzzzyj559/3sdVJm73rhRxX+i4J3vWqlXL2q8jIiKUO3duj6Zm+N/Fv5C7evWqxowZo/Tp02vAgAHOZ1q2bKlMmTLp5Zdf1uDBg9WmTRu/e2Tz/8KvA4IUN/ljyJAhKlSokJo0aaI2bdo4owGXLl3SpEmTlDt3brVv3975mWXLlnllyeC6des8RjAuXbr0wJAwePBguVwuzZ07N8Hr+j3uA9COHTuUK1cuFShQQMmTJ1epUqUUHh6umjVrqkePHtboQPny5ZUpUya1b99eN27cSPRDZ/h7fq89cZMmTTRo0CCPAyv+vPutFPn888+d92vXrq2goCCtXr3aOr4988wzeuqppzyWceOvu99++8MPP+jYsWO6ePGixo4dq6CgII9OoQMHDlRERIRKlizptPh/VPhtQIg/vHby5EkNHjxYoaGhKlu2rMfnLl26pMmTJytfvnxq3Lixx3ve7CsQv2nG/ULChQsX9NZbb/m0CUv8cJA6dWr17dtXJ0+e1NKlS1W7dm1VrFhRL730kooUKaIePXo4Q2Q3btxQhw4d9NZbb7ESAJbE1p7Yn/3RSpFy5copZ86c+uabb6zbhHw3/3enTp2S9N9J8QcPHlTmzJmdSc4XLlxwQkLfvn2dn7t165Zu377tV71sHga/DAjxd3x3E54zZ85o8ODBSp8+vQYNGuTx+cuXL2v06NFq1qyZX/QSiB8S7p396mv3a00sxS0XDQoK0okTJzRhwgSVKFFCzz77rGbMmKF+/fqpQIECftuaGL6TWNsT+6PfWyly6NAhp9dIrVq1lD17dm3YsMEvjnePivnz5ys0NNTjNur58+cVFhbm8VyZ+CHh3nPRo8bvAkL8Hf6NN95Qw4YNncYT7pAQFhbmLCd0c7f8vffv8JXLly9r6tSpcrlcHsNRvvag1sQrV65UUFCQ9u3bJ0maPn266tWrp2zZsik8PNxrz1ZA4pGY2xP7oz9aKRIcHKwmTZpIigsJ6dKlS1RzgvzdihUrVL9+fZUsWdKZ+3Hw4EHlzZvXujhyT1x0uVwaNmyYL8r1Cr8LCG59+/ZVlixZNGPGDI/0durUKQ0ePFj58uXT0KFDrZ/zh6t0t0uXLmn69Ol+tx7W3SugRo0a2rt3r65evarHH3/cY8hMiqv/xIkTjBzggRJje2J/9WdWiuTIkcN5nku1atWcSaJ4OKKiotSoUSMVLVpU33//vY4cOaLMmTPft528ew6cPz5b5GFxSZLxM6tWrTJt2rQxixYtMqVLlzaSzMWLF83Ro0dN3rx5jcvlMqNHjzZjx441//nPf8yLL77o65IfSJJxuVy+LsNy4MAB06NHD3P9+nWzc+dO88ILL5gxY8YYY4y5e/euSZYsmY8rBP551qxZY2rWrGmyZctmLly4YEaNGmWqVatm8uTJY+7cuWPq1atnHnvsMTN79mxfl/pIiX+cjoqKMuPGjTMnTpwwnTt3NrNmzTI1a9Y0oaGhJjY21ty5c8fcunXLFCxY0JQpU8bHlScsvzwLXLx40WTNmtWUKlXKbNu2zSxdutTMnj3bXLlyxVStWtW89957pl27diY4ONi88MILvi73d/ljODDGmLx585px48aZzp07m7Rp05pGjRo57yVNmtSHlQH/XFWrVjWHDh0yZ8+eNTly5DAZM2Z03kuaNKlJly6dyZ07t4mNjTXGGJMkSRJflfpIiX+crly5srl7966ZNGmS6d+/vzl//rxJmzatmTFjhnG5XCZFihQmJibGfPbZZz6s2Dt8PoJw48YNkypVKo/Xtm/fbooVK2Zq1aplNm/ebOrVq2eqVKliAgICzEsvvWS++OILj+QWExPDSe1v+uWXX0y3bt2MJPPaa6+ZcuXK+bokAPe4ffu2efPNN81HH31koqKiTN68eX1d0iPBPXKwbds28+uvv5rY2FhTt25dY4wxq1evNh999JHZuXOnmTlzpgkPD3d+Ljo62vzrX//yVdle49OA8Omnn5qDBw+aAQMGmICAACPJxMbGmqRJk5oNGzaYBQsWmKefftpUrVrVPP744yY6OtpUqlTJjBw50lStWtVXZT9yDhw4YHr16mXOnTtnxowZY55++mlflwTg/5s5c6bZvHmzmTdvnlm+fLkpWrSor0t6pCxcuNC0adPGPPHEE+bUqVMmIiLCfPLJJ8aYuJAwfvx4c+bMGTN8+HBTpUoVY4z/3jp+6Hwy80HSlClT5HK5tHz5ckmeXas2b96so0ePOp+9ffu2rly5olq1aqlMmTKP3FpTf7Bv3z41adLEY7sD8C1WiiQM97kmOjpaFStW1CeffKJDhw7pyy+/1GOPPaaGDRs6n42KilLVqlVVqVKlf1ynSp+MIHz66aemXbt2ZsmSJaZOnTrGXYLL5TKLFi0yHTt2NAsXLjSVKlUyd+7cMRMmTDALFiwwt2/fNhs2bDDJkyc3sbGx3H97yG7fvm1SpEjh6zIAxHP27FkTEBBg0qVL5+tSHimrVq0yn376qUmaNKkZMWKEyZQpkzHGmA0bNpiGDRua8uXLm0WLFhmXy2W++eYbExoaaoKDg31ctXd5/Qw7ffp088ILL5jKlSubOnXqGGOMiY2NNS6XyyxZssQ0adLEDBs2zFSqVMkYExcawsPDTfXq1c13331nkidPbu7evUs4SACEA8D/ZMqUiXCQAC5cuGAWLFhgli9f7qzakmTKlStnlixZYjZt2mSqV69uJJkKFSr848KBMV4OCFOnTjXt2rUz7dq1M3v27DE9evQwxsTNzpVk7ty5YyZPnmw6d+7s/EyyZMlMlSpVzJAhQ0yyZMlMTEwMS/AAAH/Ivdrjfn9u1KiRmTVrlomOjjaDBg0yxvx3NUO5cuXM7NmzzbFjx8zJkye9V7Cf8dothrFjx5pevXqZL7/80tSuXdtMmTLFDBo0yLRs2dKMGzfOGyUAAP5hfvrpJ/Ppp5+ajh07muzZs3tMLrxz545ZvHixadOmjWnfvr0ZP368x8/eb5XdP4nXAsK6devM6dOnTfPmzY0xxly+fNnMmzfPDBw40CMksGQRAPAw3Llzx5QrV85s2bLF5MmTx/z73/82pUqVMk2bNnU+c/PmTbN06VLTpk0b07lzZ6dhHLzYKMk9p0D/f3lIunTpnLAwcOBAY4wx48aNM0mTJiUkAAD+Z8mTJzdNmzY1LVq0MIUKFTIbNmwwnTp1MsuWLTNlypQxnTt3NilTpjTPPvusMcaYFi1amBQpUpgRI0b4uHL/4PNGSVeuXDFz5841gwYNMq1atSK9AQAemqioKPPvf//brF692pQoUcKcPn3afPDBB2bkyJGmcOHCpl27dqZKlSomT548ZvHixSZ//vwmLCzM12X7BZ8HBGPiQsK8efNMp06dzJgxY5zJiwAA/K/69OljTp8+baZNm2ZSpkxpmjdvbnbs2GFKly5tDh8+bDZu3GhGjRplunfv/s9ogPQn+cVygLRp05qmTZuaTJkymXr16vm6HADAI6R06dLm3XffNSlSpDDt27c3UVFRZvXq1aZgwYLm559/NitWrDDVqlUjHNzDL0YQ7sXTBAEAD1OlSpXMt99+a5544gnz1VdfeTxbAffnl92GCAcAgIfBfQ3cr18/kydPHjNhwgQTHh5u/PDa2O/4ZUAAAOBhcN82KF68uImNjTVbt271eB0PRkAAADzyMmfObAYPHmzGjBljfvjhB1+XkygQEAAA/whVqlQxJUuWNFmzZvV1KYmCX05SBAAgIdy8edOkTJnS12UkCgQEAABg4RYDAACwEBAAAICFgAAAACwEBAAAYCEgAAAACwEBAABYCAgAAMBCQAAAABYCAgAAsPw/z+vVOmqSRZQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_value_array(1, predictions_single[0], test_labels)\n",
    "_ = plt.xticks(range(10), class_names, rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cU1Y2OAMCaXb"
   },
   "source": [
    "`tf.keras.Model.predict` は、リストのリストを返します。リストの要素のそれぞれが、バッチの中の画像に対応します。バッチの中から、(といってもバッチの中身は１つだけですが) 予測を取り出します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-15T00:32:14.258142Z",
     "iopub.status.busy": "2022-12-15T00:32:14.257491Z",
     "iopub.status.idle": "2022-12-15T00:32:14.262230Z",
     "shell.execute_reply": "2022-12-15T00:32:14.261509Z"
    },
    "id": "2tRmdq_8CaXb"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(predictions_single[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YFc2HbEVCaXd"
   },
   "source": [
    "モデルは期待どおりにラベルを予測しました。"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "classification.ipynb",
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}