{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ndo4ERqnwQOU"
   },
   "source": [
    "##### Copyright 2024 The TensorFlow Authors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "13rwRG5Jec7n"
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:37.646930Z",
     "iopub.status.busy": "2024-07-19T01:34:37.646708Z",
     "iopub.status.idle": "2024-07-19T01:34:37.650485Z",
     "shell.execute_reply": "2024-07-19T01:34:37.649798Z"
    },
    "id": "MTKwbguKwT4R"
   },
   "outputs": [],
   "source": [
    "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "# https://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xfNT-mlFwxVM"
   },
   "source": [
    "# Intro to Autoencoders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0TD5ZrvEMbhZ"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/generative/autoencoder\">\n",
    "    <img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />\n",
    "    View on TensorFlow.org</a>\n",
    "  </td>\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/generative/autoencoder.ipynb\">\n",
    "    <img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />\n",
    "    Run in Google Colab</a>\n",
    "  </td>\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/en/tutorials/generative/autoencoder.ipynb\">\n",
    "    <img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />\n",
    "    View source on GitHub</a>\n",
    "  </td>\n",
    "  <td>\n",
    "    <a href=\"https://storage.googleapis.com/tensorflow_docs/docs/site/en/tutorials/generative/autoencoder.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\" />Download notebook</a>\n",
    "  </td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ITZuApL56Mny"
   },
   "source": [
    "This tutorial introduces autoencoders with three examples: the basics, image denoising, and anomaly detection.\n",
    "\n",
    "An autoencoder is a special type of neural network that is trained to copy its input to its output. For example, given an image of a handwritten digit, an autoencoder first encodes the image into a lower dimensional latent representation, then decodes the latent representation back to an image. An autoencoder learns to compress the data while minimizing the reconstruction error.\n",
    "\n",
    "To learn more about autoencoders, please consider reading chapter 14 from [Deep Learning](https://www.deeplearningbook.org/) by Ian Goodfellow, Yoshua Bengio, and Aaron Courville."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e1_Y75QXJS6h"
   },
   "source": [
    "## Import TensorFlow and other libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:37.654144Z",
     "iopub.status.busy": "2024-07-19T01:34:37.653768Z",
     "iopub.status.idle": "2024-07-19T01:34:40.549987Z",
     "shell.execute_reply": "2024-07-19T01:34:40.549253Z"
    },
    "id": "YfIk2es3hJEd"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-07-19 01:34:38.577118: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
      "2024-07-19 01:34:38.597940: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
      "2024-07-19 01:34:38.604259: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras import layers, losses\n",
    "from tensorflow.keras.datasets import fashion_mnist\n",
    "from tensorflow.keras.models import Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iYn4MdZnKCey"
   },
   "source": [
    "## Load the dataset\n",
    "To start, you will train the basic autoencoder using the Fashion MNIST dataset. Each image in this dataset is 28x28 pixels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:40.554420Z",
     "iopub.status.busy": "2024-07-19T01:34:40.553994Z",
     "iopub.status.idle": "2024-07-19T01:34:41.751480Z",
     "shell.execute_reply": "2024-07-19T01:34:41.750697Z"
    },
    "id": "YZm503-I_tji"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m    0/29515\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0s/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m29515/29515\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m       0/26421880\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0s/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 4202496/26421880\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0us/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m11640832/26421880\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0us/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m16785408/26421880\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0us/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m26421880/26421880\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   0/5148\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0s/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5148/5148\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m      0/4422102\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 0s/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m4422102/4422102\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60000, 28, 28)\n",
      "(10000, 28, 28)\n"
     ]
    }
   ],
   "source": [
    "(x_train, _), (x_test, _) = fashion_mnist.load_data()\n",
    "\n",
    "x_train = x_train.astype('float32') / 255.\n",
    "x_test = x_test.astype('float32') / 255.\n",
    "\n",
    "print (x_train.shape)\n",
    "print (x_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VEdCXSwCoKok"
   },
   "source": [
    "## First example: Basic autoencoder\n",
    "![Basic autoencoder results](images/intro_autoencoder_result.png)\n",
    "\n",
    "Define an autoencoder with two Dense layers: an `encoder`, which compresses the images into a 64 dimensional latent vector, and a `decoder`, that reconstructs the original image from the latent space.\n",
    "\n",
    "To define your model, use the [Keras Model Subclassing API](https://www.tensorflow.org/guide/keras/custom_layers_and_models).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:41.755139Z",
     "iopub.status.busy": "2024-07-19T01:34:41.754867Z",
     "iopub.status.idle": "2024-07-19T01:34:44.012252Z",
     "shell.execute_reply": "2024-07-19T01:34:44.011113Z"
    },
    "id": "0MUxidpyChjX"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1721352882.295547   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.299415   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.302977   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.306555   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.317911   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.321456   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.324803   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.328236   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.331593   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.334951   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.338368   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352882.341848   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.589512   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.591771   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.593770   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.595852   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.598075   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.600171   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.602045   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.604032   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.606144   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.608215   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.610099   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.612100   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.650350   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.652536   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.654463   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.656496   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.658633   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.660717   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.662587   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.664545   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.666746   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.669465   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.671789   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "I0000 00:00:1721352883.674211   23008 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n"
     ]
    }
   ],
   "source": [
    "class Autoencoder(Model):\n",
    "  def __init__(self, latent_dim, shape):\n",
    "    super(Autoencoder, self).__init__()\n",
    "    self.latent_dim = latent_dim\n",
    "    self.shape = shape\n",
    "    self.encoder = tf.keras.Sequential([\n",
    "      layers.Flatten(),\n",
    "      layers.Dense(latent_dim, activation='relu'),\n",
    "    ])\n",
    "    self.decoder = tf.keras.Sequential([\n",
    "      layers.Dense(tf.math.reduce_prod(shape).numpy(), activation='sigmoid'),\n",
    "      layers.Reshape(shape)\n",
    "    ])\n",
    "\n",
    "  def call(self, x):\n",
    "    encoded = self.encoder(x)\n",
    "    decoded = self.decoder(encoded)\n",
    "    return decoded\n",
    "\n",
    "\n",
    "shape = x_test.shape[1:]\n",
    "latent_dim = 64\n",
    "autoencoder = Autoencoder(latent_dim, shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:44.015853Z",
     "iopub.status.busy": "2024-07-19T01:34:44.015572Z",
     "iopub.status.idle": "2024-07-19T01:34:44.032070Z",
     "shell.execute_reply": "2024-07-19T01:34:44.031103Z"
    },
    "id": "9I1JlqEIDCI4"
   },
   "outputs": [],
   "source": [
    "autoencoder.compile(optimizer='adam', loss=losses.MeanSquaredError())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7oJSeMTroABs"
   },
   "source": [
    "Train the model using `x_train` as both the input and the target. The `encoder` will learn to compress the dataset from 784 dimensions to the latent space, and the `decoder` will learn to reconstruct the original images.\n",
    "."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:34:44.035747Z",
     "iopub.status.busy": "2024-07-19T01:34:44.035280Z",
     "iopub.status.idle": "2024-07-19T01:35:10.996951Z",
     "shell.execute_reply": "2024-07-19T01:35:10.996136Z"
    },
    "id": "h1RI9OfHDBsK"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1721352885.729397   23175 service.cc:146] XLA service 0x7fbe4c008de0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
      "I0000 00:00:1721352885.729441   23175 service.cc:154]   StreamExecutor device (0): Tesla T4, Compute Capability 7.5\n",
      "I0000 00:00:1721352885.729445   23175 service.cc:154]   StreamExecutor device (1): Tesla T4, Compute Capability 7.5\n",
      "I0000 00:00:1721352885.729448   23175 service.cc:154]   StreamExecutor device (2): Tesla T4, Compute Capability 7.5\n",
      "I0000 00:00:1721352885.729451   23175 service.cc:154]   StreamExecutor device (3): Tesla T4, Compute Capability 7.5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m43:44\u001b[0m 1s/step - loss: 0.1727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  44/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.1374  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  93/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1144"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 142/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1013"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "I0000 00:00:1721352886.371904   23175 device_compiler.h:188] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 190/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0925"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 237/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0862"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 284/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0811"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 332/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 380/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 428/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 477/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0677"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 525/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 573/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 621/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 669/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 718/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 765/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 813/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0557"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 861/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0545"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 908/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0534"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 956/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0524"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1005/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0514"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1053/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0505"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1102/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0496"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1150/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0488"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1199/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0480"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1248/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0473"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1296/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0466"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1344/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0460"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1392/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0453"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1441/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0447"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1490/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0441"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1537/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0436"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1584/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0431"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1631/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0426"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1679/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0421"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1726/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0416"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1774/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0412"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1821/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0407"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1869/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0403"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0403 - val_loss: 0.0132\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:33\u001b[0m 50ms/step - loss: 0.0129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  42/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0134   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  88/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0133"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 137/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0132"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 185/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0131"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 234/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0131"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 282/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0131"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 330/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0130"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 378/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0130"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 426/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 474/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 522/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0129"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 570/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0128"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 618/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0128"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 666/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0128"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 714/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0128"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 762/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 809/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 855/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 902/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0127"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 949/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 994/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1039/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1086/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1133/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1180/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1228/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1275/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1322/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1370/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1417/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1464/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1511/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1558/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1606/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1651/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1695/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1742/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1789/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1836/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0123"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0123 - val_loss: 0.0106\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:24\u001b[0m 45ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  47/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  94/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 141/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 188/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 235/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 282/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 328/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 375/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0104"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 421/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 467/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 514/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 561/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 607/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 654/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 701/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 748/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 795/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 842/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 890/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 937/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 983/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1030/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1076/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1123/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1169/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1215/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1261/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1309/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1356/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1404/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1451/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1496/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1542/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1588/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1635/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1682/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1729/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1776/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1824/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1873/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0102"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0102 - val_loss: 0.0097\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:26\u001b[0m 46ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  48/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0097   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  97/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 146/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 194/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 243/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 291/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 339/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 389/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 438/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 487/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 536/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 584/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 632/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 680/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 728/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0096"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 777/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 825/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 873/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 922/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 972/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1020/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1069/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1118/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1167/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1217/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1266/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1314/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1362/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1411/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1460/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1508/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1556/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1604/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1653/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1702/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1751/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1799/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1848/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0095 - val_loss: 0.0093\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:25\u001b[0m 46ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  47/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0090   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  95/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 144/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 193/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 241/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 288/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 335/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 383/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 430/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 477/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 524/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 570/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 615/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 662/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 710/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 758/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 805/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 851/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 897/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 945/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 992/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1039/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1088/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1136/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1184/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1231/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1279/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1328/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1376/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1424/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1472/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1520/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1569/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1616/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1662/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1710/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1759/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1808/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1855/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0092 - val_loss: 0.0093\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:25\u001b[0m 46ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  46/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0091   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  93/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 140/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 187/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 235/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 283/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 331/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 378/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 425/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 471/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 518/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 566/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 614/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 662/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 710/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 758/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 804/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 848/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 893/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 938/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 983/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1030/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1077/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1121/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1166/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1211/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1256/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1301/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1347/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1393/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1438/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1484/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1530/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1576/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1623/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1714/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1759/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1803/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1848/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0090 - val_loss: 0.0090\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:28\u001b[0m 47ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  45/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  91/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 136/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 181/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 228/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 274/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 321/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 367/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 411/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 456/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 500/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 545/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 591/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 636/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 681/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 727/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 774/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 821/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 868/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 915/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 962/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1010/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1056/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1103/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1150/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1198/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1245/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1292/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1339/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1384/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1430/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1476/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1521/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1567/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1611/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1656/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1701/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1746/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1791/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1836/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088 - val_loss: 0.0090\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:25\u001b[0m 46ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  45/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  89/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 133/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 178/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 224/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 270/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 316/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 362/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 409/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 457/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 503/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 550/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 595/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 640/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 685/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 732/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 778/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 825/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 870/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 916/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 958/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1001/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1044/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1089/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1134/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1178/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1224/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1270/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1318/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1366/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1413/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1462/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1510/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1557/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1605/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1651/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1696/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1740/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1785/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1830/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088 - val_loss: 0.0089\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:29\u001b[0m 48ms/step - loss: 0.0075"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  46/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  93/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 139/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 186/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 233/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 281/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 327/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 375/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 422/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 469/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 515/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 561/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 607/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 654/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 702/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 750/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 798/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 845/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 893/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 941/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 989/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1036/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1081/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1128/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1175/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1223/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1271/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1318/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1366/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1413/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1459/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1504/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1549/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1592/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1635/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1682/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1730/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1777/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1824/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1871/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0088 - val_loss: 0.0088\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:27\u001b[0m 47ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  48/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0085   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  95/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 142/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 187/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 234/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 281/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 327/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 374/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 421/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 468/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 515/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 562/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 610/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 656/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 702/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 750/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 797/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 846/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 893/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 940/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 987/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1035/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1082/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1130/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1178/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1225/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1272/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1318/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1361/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1405/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1450/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1496/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1543/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1591/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1639/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1687/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1735/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1784/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1833/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0087 - val_loss: 0.0088\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fc008462fa0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "autoencoder.fit(x_train, x_train,\n",
    "                epochs=10,\n",
    "                shuffle=True,\n",
    "                validation_data=(x_test, x_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wAM1QBhtoC-n"
   },
   "source": [
    "Now that the model is trained, let's test it by encoding and decoding images from the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:11.000699Z",
     "iopub.status.busy": "2024-07-19T01:35:11.000085Z",
     "iopub.status.idle": "2024-07-19T01:35:11.169653Z",
     "shell.execute_reply": "2024-07-19T01:35:11.168855Z"
    },
    "id": "Pbr5WCj7FQUi"
   },
   "outputs": [],
   "source": [
    "encoded_imgs = autoencoder.encoder(x_test).numpy()\n",
    "decoded_imgs = autoencoder.decoder(encoded_imgs).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:11.173631Z",
     "iopub.status.busy": "2024-07-19T01:35:11.173354Z",
     "iopub.status.idle": "2024-07-19T01:35:11.561879Z",
     "shell.execute_reply": "2024-07-19T01:35:11.561232Z"
    },
    "id": "s4LlDOS6FUA1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x400 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 10\n",
    "plt.figure(figsize=(20, 4))\n",
    "for i in range(n):\n",
    "  # display original\n",
    "  ax = plt.subplot(2, n, i + 1)\n",
    "  plt.imshow(x_test[i])\n",
    "  plt.title(\"original\")\n",
    "  plt.gray()\n",
    "  ax.get_xaxis().set_visible(False)\n",
    "  ax.get_yaxis().set_visible(False)\n",
    "\n",
    "  # display reconstruction\n",
    "  ax = plt.subplot(2, n, i + 1 + n)\n",
    "  plt.imshow(decoded_imgs[i])\n",
    "  plt.title(\"reconstructed\")\n",
    "  plt.gray()\n",
    "  ax.get_xaxis().set_visible(False)\n",
    "  ax.get_yaxis().set_visible(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "r4gv6G8PoRQE"
   },
   "source": [
    "## Second example: Image denoising\n",
    "\n",
    "\n",
    "![Image denoising results](images/image_denoise_fmnist_results.png)\n",
    "\n",
    "An autoencoder can also be trained to remove noise from images. In the following section, you will create a noisy version of the Fashion MNIST dataset by applying random noise to each image. You will then train an autoencoder using the noisy image as input, and the original image as the target.\n",
    "\n",
    "Let's reimport the dataset to omit the modifications made earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:11.565605Z",
     "iopub.status.busy": "2024-07-19T01:35:11.565368Z",
     "iopub.status.idle": "2024-07-19T01:35:11.923382Z",
     "shell.execute_reply": "2024-07-19T01:35:11.922615Z"
    },
    "id": "gDYHJA2PCQ3m"
   },
   "outputs": [],
   "source": [
    "(x_train, _), (x_test, _) = fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:11.927244Z",
     "iopub.status.busy": "2024-07-19T01:35:11.926988Z",
     "iopub.status.idle": "2024-07-19T01:35:12.016222Z",
     "shell.execute_reply": "2024-07-19T01:35:12.015435Z"
    },
    "id": "uJZ-TcaqDBr5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60000, 28, 28, 1)\n"
     ]
    }
   ],
   "source": [
    "x_train = x_train.astype('float32') / 255.\n",
    "x_test = x_test.astype('float32') / 255.\n",
    "\n",
    "x_train = x_train[..., tf.newaxis]\n",
    "x_test = x_test[..., tf.newaxis]\n",
    "\n",
    "print(x_train.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aPZl_6P65_8R"
   },
   "source": [
    "Adding random noise to the images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:12.019613Z",
     "iopub.status.busy": "2024-07-19T01:35:12.019359Z",
     "iopub.status.idle": "2024-07-19T01:35:12.961380Z",
     "shell.execute_reply": "2024-07-19T01:35:12.960623Z"
    },
    "id": "axSMyxC354fc"
   },
   "outputs": [],
   "source": [
    "noise_factor = 0.2\n",
    "x_train_noisy = x_train + noise_factor * tf.random.normal(shape=x_train.shape)\n",
    "x_test_noisy = x_test + noise_factor * tf.random.normal(shape=x_test.shape)\n",
    "\n",
    "x_train_noisy = tf.clip_by_value(x_train_noisy, clip_value_min=0., clip_value_max=1.)\n",
    "x_test_noisy = tf.clip_by_value(x_test_noisy, clip_value_min=0., clip_value_max=1.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wRxHe4XXltNd"
   },
   "source": [
    "Plot the noisy images.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:12.965417Z",
     "iopub.status.busy": "2024-07-19T01:35:12.965142Z",
     "iopub.status.idle": "2024-07-19T01:35:13.605268Z",
     "shell.execute_reply": "2024-07-19T01:35:13.604315Z"
    },
    "id": "thKUmbVVCQpt"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x200 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 10\n",
    "plt.figure(figsize=(20, 2))\n",
    "for i in range(n):\n",
    "    ax = plt.subplot(1, n, i + 1)\n",
    "    plt.title(\"original + noise\")\n",
    "    plt.imshow(tf.squeeze(x_test_noisy[i]))\n",
    "    plt.gray()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Sy9SY8jGl5aP"
   },
   "source": [
    "### Define a convolutional autoencoder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vT_BhZngWMwp"
   },
   "source": [
    "In this example, you will train a convolutional autoencoder using  [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D) layers in the `encoder`, and [Conv2DTranspose](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2DTranspose) layers in the `decoder`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:13.608850Z",
     "iopub.status.busy": "2024-07-19T01:35:13.608591Z",
     "iopub.status.idle": "2024-07-19T01:35:13.635958Z",
     "shell.execute_reply": "2024-07-19T01:35:13.635319Z"
    },
    "id": "R5KjoIlYCQko"
   },
   "outputs": [],
   "source": [
    "class Denoise(Model):\n",
    "  def __init__(self):\n",
    "    super(Denoise, self).__init__()\n",
    "    self.encoder = tf.keras.Sequential([\n",
    "      layers.Input(shape=(28, 28, 1)),\n",
    "      layers.Conv2D(16, (3, 3), activation='relu', padding='same', strides=2),\n",
    "      layers.Conv2D(8, (3, 3), activation='relu', padding='same', strides=2)])\n",
    "\n",
    "    self.decoder = tf.keras.Sequential([\n",
    "      layers.Conv2DTranspose(8, kernel_size=3, strides=2, activation='relu', padding='same'),\n",
    "      layers.Conv2DTranspose(16, kernel_size=3, strides=2, activation='relu', padding='same'),\n",
    "      layers.Conv2D(1, kernel_size=(3, 3), activation='sigmoid', padding='same')])\n",
    "\n",
    "  def call(self, x):\n",
    "    encoded = self.encoder(x)\n",
    "    decoded = self.decoder(encoded)\n",
    "    return decoded\n",
    "\n",
    "autoencoder = Denoise()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:13.639116Z",
     "iopub.status.busy": "2024-07-19T01:35:13.638868Z",
     "iopub.status.idle": "2024-07-19T01:35:13.645053Z",
     "shell.execute_reply": "2024-07-19T01:35:13.644339Z"
    },
    "id": "QYKbiDFYCQfj"
   },
   "outputs": [],
   "source": [
    "autoencoder.compile(optimizer='adam', loss=losses.MeanSquaredError())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:13.648076Z",
     "iopub.status.busy": "2024-07-19T01:35:13.647844Z",
     "iopub.status.idle": "2024-07-19T01:35:53.910483Z",
     "shell.execute_reply": "2024-07-19T01:35:53.909766Z"
    },
    "id": "IssFr1BNCQX3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:27:36\u001b[0m 3s/step - loss: 0.1733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  32/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.1652    "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  65/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  98/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1463"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 132/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1339"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 166/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1231"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 201/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1140"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 236/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1064"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 270/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1002"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 304/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0948"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 338/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 373/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0861"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 408/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 441/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 474/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0766"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 508/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 542/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 577/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 611/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0675"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 644/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 678/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 712/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 746/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 780/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 814/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 848/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 882/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0560"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 916/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0549"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 951/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0539"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 986/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0529"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1021/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0520"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1056/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0511"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1090/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0503"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1123/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0496"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1157/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0488"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1191/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0481"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1226/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0474"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1261/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0467"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1295/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0461"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1330/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0455"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1364/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0449"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1398/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0444"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1432/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0438"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1466/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0433"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1500/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0428"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1534/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0424"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1568/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0419"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1602/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0414"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1636/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0410"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0406"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1704/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0402"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1738/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0398"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1772/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0394"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1805/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0391"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1840/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0387"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1874/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0383"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 2ms/step - loss: 0.0383 - val_loss: 0.0111\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:28\u001b[0m 47ms/step - loss: 0.0125"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  33/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0112   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  65/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0111"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  97/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 130/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 163/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 196/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 229/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 262/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0110"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 294/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 327/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 360/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 393/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 426/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 458/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 490/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 522/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 555/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 588/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 621/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 653/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 685/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 718/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0109"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 750/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 782/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 815/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 848/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 881/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 913/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 944/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 975/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1006/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1037/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1068/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1099/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1129/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1159/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1189/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1219/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1249/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1279/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1310/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1340/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0108"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1369/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1399/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1431/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1462/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1492/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1522/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1552/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1582/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1611/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1640/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1700/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1730/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1760/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1790/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1821/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1853/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0107"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0107 - val_loss: 0.0099\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:25\u001b[0m 46ms/step - loss: 0.0105"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  30/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0097   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  58/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  86/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 115/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 144/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 173/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 202/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 230/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 258/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 286/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 315/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 344/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 373/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 402/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 431/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 459/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 488/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 517/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 545/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 574/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 603/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 631/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 661/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 691/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 721/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 751/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 781/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 810/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 838/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 867/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 895/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 923/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 952/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 980/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1009/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1037/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1065/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1093/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1121/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1150/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1178/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1206/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1234/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1262/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1289/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1317/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1345/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1373/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1401/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1429/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1457/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1486/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0098"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1514/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1542/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1570/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1598/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1626/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1655/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1683/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1712/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1740/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1768/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1796/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1824/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1853/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0097"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0097 - val_loss: 0.0094\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:27\u001b[0m 47ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  28/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  55/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  82/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 109/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 136/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 163/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 190/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 217/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 244/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 272/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 299/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 326/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 353/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 380/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 407/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 435/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 463/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 491/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 519/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 547/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 575/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 603/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 631/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 659/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 687/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 714/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 742/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 770/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 797/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 825/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 853/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 880/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 907/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 934/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 962/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 990/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1018/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1046/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1074/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1102/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1130/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1158/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1186/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1214/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1242/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1270/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1297/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1325/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1353/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1381/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1409/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1436/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1464/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1492/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1520/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1547/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1575/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1602/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1630/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1658/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1686/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1714/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1742/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1770/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1798/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1826/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1854/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0093"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0093 - val_loss: 0.0091\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:29\u001b[0m 48ms/step - loss: 0.0100"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  30/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0093   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  60/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  89/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 119/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 149/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 178/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 207/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 236/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 266/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0091"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 296/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 326/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 355/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 384/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 413/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 442/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 472/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 501/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 530/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 560/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 589/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 619/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 649/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 678/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 707/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 737/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 767/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 796/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 825/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 855/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 884/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 914/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 944/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0090"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 974/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1004/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1033/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1062/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1091/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1121/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1151/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1182/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1212/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1243/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1273/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1303/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1334/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1363/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1393/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1423/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1453/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1484/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1514/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1544/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1574/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1603/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1633/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1663/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1693/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1723/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1753/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1783/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1813/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1843/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1874/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0089"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0089 - val_loss: 0.0087\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:26\u001b[0m 46ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  31/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0086   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  62/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  93/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 123/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 153/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 183/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0086"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 213/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 243/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 273/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 303/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 333/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 363/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 393/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 423/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 453/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 483/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 513/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 543/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 573/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 603/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 632/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 662/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 692/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 722/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 752/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 782/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 812/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 842/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 872/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 902/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 932/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 962/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 992/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1022/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1052/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1082/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1112/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1142/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1172/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1202/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1232/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0085"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1262/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1290/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1318/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1347/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1377/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1408/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1439/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1470/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1501/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1532/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1563/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1594/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1625/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1656/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1687/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1718/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1749/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1780/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1811/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1842/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1874/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0084"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0084 - val_loss: 0.0082\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:25\u001b[0m 46ms/step - loss: 0.0088"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  32/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0084   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  64/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0083"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  95/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 127/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 158/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 188/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 219/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 250/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 282/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 313/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 345/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 376/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 407/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 437/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 468/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 499/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 530/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 561/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 592/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 623/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 654/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 685/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 716/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 747/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 778/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 809/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 840/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 872/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 903/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 934/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 966/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 998/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1029/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1061/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1093/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1125/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1156/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1187/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1219/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1251/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1283/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1315/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1347/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1379/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1411/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1443/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1475/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1507/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1539/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1571/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1603/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1635/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1667/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1699/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1731/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1762/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1794/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1825/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1856/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0081 - val_loss: 0.0080\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:29\u001b[0m 48ms/step - loss: 0.0083"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  30/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  60/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  90/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 120/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 149/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 178/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 208/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 238/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 268/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 298/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 328/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 358/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 388/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 418/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 448/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 478/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 508/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 538/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 569/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 599/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 629/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 659/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 689/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 719/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 750/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 781/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 811/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 841/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 871/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 902/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 932/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 962/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 993/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1022/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1051/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1080/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1110/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1139/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1168/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1197/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1226/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1255/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1285/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1315/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1345/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1375/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1404/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1434/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1464/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1493/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1523/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1552/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1581/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1610/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1640/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1700/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1730/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1759/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1789/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1819/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1849/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0079 - val_loss: 0.0078\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:28\u001b[0m 47ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  29/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0082   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  57/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0082"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  85/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 113/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0081"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 141/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 170/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 198/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 228/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 258/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 288/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 317/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 345/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 373/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0080"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 402/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 431/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 460/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 488/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 517/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 546/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 575/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 604/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 633/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 662/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 691/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 720/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 749/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 778/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 807/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 835/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 864/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 893/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 923/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 953/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 982/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1011/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1040/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1068/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1097/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1127/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1156/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1184/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1213/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1241/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1270/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1298/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1327/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1356/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1385/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1413/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1442/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1470/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1498/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1527/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1557/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1585/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1613/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1641/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1699/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1727/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1756/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1785/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1814/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1843/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1872/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0079 - val_loss: 0.0078\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m   1/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:28\u001b[0m 47ms/step - loss: 0.0069"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  30/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0080   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  59/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m  89/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 120/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 150/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 180/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 210/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 240/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 270/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 301/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 332/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 363/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 394/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 425/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 456/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 487/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 517/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 547/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 577/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 607/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 638/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 669/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 699/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 730/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 760/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 791/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 822/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 853/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 884/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 915/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 946/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m 977/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1008/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1039/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1070/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1101/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1133/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1164/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1195/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1226/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1257/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1288/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1319/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1350/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1381/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1412/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1443/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1474/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1505/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1536/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1567/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1597/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1628/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1659/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1689/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1720/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1750/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1781/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1812/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1843/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0078 - val_loss: 0.0077\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x7fc017ac5c70>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "autoencoder.fit(x_train_noisy, x_train,\n",
    "                epochs=10,\n",
    "                shuffle=True,\n",
    "                validation_data=(x_test_noisy, x_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G85xUVBGTAKp"
   },
   "source": [
    "Let's take a look at a summary of the encoder. Notice how the images are downsampled from 28x28 to 7x7."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:53.914254Z",
     "iopub.status.busy": "2024-07-19T01:35:53.913712Z",
     "iopub.status.idle": "2024-07-19T01:35:53.926859Z",
     "shell.execute_reply": "2024-07-19T01:35:53.926255Z"
    },
    "id": "oEpxlX6sTEQz"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_2\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_2\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>)     │           <span style=\"color: #00af00; text-decoration-color: #00af00\">160</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>)        │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,160</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d (\u001b[38;5;33mConv2D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m16\u001b[0m)     │           \u001b[38;5;34m160\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_1 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m8\u001b[0m)        │         \u001b[38;5;34m1,160\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">1,320</span> (5.16 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m1,320\u001b[0m (5.16 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">1,320</span> (5.16 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m1,320\u001b[0m (5.16 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "autoencoder.encoder.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DDZBfMx1UtXx"
   },
   "source": [
    "The decoder upsamples the images back from 7x7 to 28x28."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:53.930434Z",
     "iopub.status.busy": "2024-07-19T01:35:53.929796Z",
     "iopub.status.idle": "2024-07-19T01:35:53.941815Z",
     "shell.execute_reply": "2024-07-19T01:35:53.941224Z"
    },
    "id": "pbeQtYMaUpro"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_3\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_3\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d_transpose                │ (<span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">584</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2DTranspose</span>)               │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_transpose_1              │ (<span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>)       │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,168</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2DTranspose</span>)               │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">145</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d_transpose                │ (\u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m8\u001b[0m)        │           \u001b[38;5;34m584\u001b[0m │\n",
       "│ (\u001b[38;5;33mConv2DTranspose\u001b[0m)               │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_transpose_1              │ (\u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m16\u001b[0m)       │         \u001b[38;5;34m1,168\u001b[0m │\n",
       "│ (\u001b[38;5;33mConv2DTranspose\u001b[0m)               │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_2 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m1\u001b[0m)        │           \u001b[38;5;34m145\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">1,897</span> (7.41 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m1,897\u001b[0m (7.41 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">1,897</span> (7.41 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m1,897\u001b[0m (7.41 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "autoencoder.decoder.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "A7-VAuEy_N6M"
   },
   "source": [
    "Plotting both the noisy images and the denoised images produced by the autoencoder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:53.944732Z",
     "iopub.status.busy": "2024-07-19T01:35:53.944507Z",
     "iopub.status.idle": "2024-07-19T01:35:55.125897Z",
     "shell.execute_reply": "2024-07-19T01:35:55.125206Z"
    },
    "id": "t5IyPi1fCQQz"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0000 00:00:1721352953.958381   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.977001   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.979016   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.981126   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.983229   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.986197   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.988619   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.991553   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.994704   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352953.997259   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.001698   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.004610   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.009705   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.014051   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.023790   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.038732   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.041209   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.043856   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.047107   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.050614   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.054351   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.060253   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.065635   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.070927   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.078616   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.085602   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.088252   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.090680   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.093489   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.096751   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.100334   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.137697   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.141986   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.145588   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.149917   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0000 00:00:1721352954.161306   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.165332   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.173184   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.179994   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.200042   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.216489   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.245249   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.265195   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.290166   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.314617   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.331780   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.353586   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0000 00:00:1721352954.402914   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.424736   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.554577   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.564572   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.583514   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0000 00:00:1721352954.605556   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.639923   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.654178   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.688278   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.754403   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.804660   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "W0000 00:00:1721352954.893250   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.911267   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.928996   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.951555   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.988040   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352954.998764   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352955.036812   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n",
      "W0000 00:00:1721352955.062787   23008 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n"
     ]
    }
   ],
   "source": [
    "encoded_imgs = autoencoder.encoder(x_test_noisy).numpy()\n",
    "decoded_imgs = autoencoder.decoder(encoded_imgs).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:55.129408Z",
     "iopub.status.busy": "2024-07-19T01:35:55.129134Z",
     "iopub.status.idle": "2024-07-19T01:35:55.686333Z",
     "shell.execute_reply": "2024-07-19T01:35:55.685627Z"
    },
    "id": "sfxr9NdBCP_x"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x400 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 10\n",
    "plt.figure(figsize=(20, 4))\n",
    "for i in range(n):\n",
    "\n",
    "    # display original + noise\n",
    "    ax = plt.subplot(2, n, i + 1)\n",
    "    plt.title(\"original + noise\")\n",
    "    plt.imshow(tf.squeeze(x_test_noisy[i]))\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "\n",
    "    # display reconstruction\n",
    "    bx = plt.subplot(2, n, i + n + 1)\n",
    "    plt.title(\"reconstructed\")\n",
    "    plt.imshow(tf.squeeze(decoded_imgs[i]))\n",
    "    plt.gray()\n",
    "    bx.get_xaxis().set_visible(False)\n",
    "    bx.get_yaxis().set_visible(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ErGrTnWHoUYl"
   },
   "source": [
    "## Third example: Anomaly detection\n",
    "\n",
    "## Overview\n",
    "\n",
    "\n",
    "In this example, you will train an autoencoder to detect anomalies on the [ECG5000 dataset](http://www.timeseriesclassification.com/description.php?Dataset=ECG5000). This dataset contains 5,000 [Electrocardiograms](https://en.wikipedia.org/wiki/Electrocardiography), each with 140 data points. You will use a simplified version of the dataset, where each example has been labeled either `0` (corresponding to an abnormal rhythm), or `1` (corresponding to a normal rhythm). You are interested in identifying the abnormal rhythms.\n",
    "\n",
    "Note: This is a labeled dataset, so you could phrase this as a supervised learning problem. The goal of this example is to illustrate anomaly detection concepts you can apply to larger datasets, where you do not have labels available (for example, if you had many thousands of normal rhythms, and only a small number of abnormal rhythms).\n",
    "\n",
    "How will you detect anomalies using an autoencoder? Recall that an autoencoder is trained to minimize reconstruction error. You will train an autoencoder on the normal rhythms only, then use it to reconstruct all the data. Our hypothesis is that the abnormal rhythms will have higher reconstruction error. You will then classify a rhythm as an anomaly if the reconstruction error surpasses a fixed threshold."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "i5estNaur_Mh"
   },
   "source": [
    "### Load ECG data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "y35nsXLPsDNX"
   },
   "source": [
    "The dataset you will use is based on one from [timeseriesclassification.com](http://www.timeseriesclassification.com/description.php?Dataset=ECG5000).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:55.690272Z",
     "iopub.status.busy": "2024-07-19T01:35:55.690006Z",
     "iopub.status.idle": "2024-07-19T01:35:56.052358Z",
     "shell.execute_reply": "2024-07-19T01:35:56.051696Z"
    },
    "id": "KmKRDJWgsFYa"
   },
   "outputs": [
    {
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       "\n",
       "[5 rows x 141 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Download the dataset\n",
    "dataframe = pd.read_csv('http://storage.googleapis.com/download.tensorflow.org/data/ecg.csv', header=None)\n",
    "raw_data = dataframe.values\n",
    "dataframe.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.055385Z",
     "iopub.status.busy": "2024-07-19T01:35:56.055146Z",
     "iopub.status.idle": "2024-07-19T01:35:56.062191Z",
     "shell.execute_reply": "2024-07-19T01:35:56.061620Z"
    },
    "id": "UmuCPVYKsKKx"
   },
   "outputs": [],
   "source": [
    "# The last element contains the labels\n",
    "labels = raw_data[:, -1]\n",
    "\n",
    "# The other data points are the electrocadriogram data\n",
    "data = raw_data[:, 0:-1]\n",
    "\n",
    "train_data, test_data, train_labels, test_labels = train_test_split(\n",
    "    data, labels, test_size=0.2, random_state=21\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "byK2vP7hsMbz"
   },
   "source": [
    "Normalize the data to `[0,1]`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.065392Z",
     "iopub.status.busy": "2024-07-19T01:35:56.065132Z",
     "iopub.status.idle": "2024-07-19T01:35:56.089509Z",
     "shell.execute_reply": "2024-07-19T01:35:56.088823Z"
    },
    "id": "tgMZVWRKsPx6"
   },
   "outputs": [],
   "source": [
    "min_val = tf.reduce_min(train_data)\n",
    "max_val = tf.reduce_max(train_data)\n",
    "\n",
    "train_data = (train_data - min_val) / (max_val - min_val)\n",
    "test_data = (test_data - min_val) / (max_val - min_val)\n",
    "\n",
    "train_data = tf.cast(train_data, tf.float32)\n",
    "test_data = tf.cast(test_data, tf.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BdSYr2IPsTiz"
   },
   "source": [
    "You will train the autoencoder using only the normal rhythms, which are labeled in this dataset as `1`. Separate the normal rhythms from the abnormal rhythms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.092796Z",
     "iopub.status.busy": "2024-07-19T01:35:56.092548Z",
     "iopub.status.idle": "2024-07-19T01:35:56.119786Z",
     "shell.execute_reply": "2024-07-19T01:35:56.119169Z"
    },
    "id": "VvK4NRe8sVhE"
   },
   "outputs": [],
   "source": [
    "train_labels = train_labels.astype(bool)\n",
    "test_labels = test_labels.astype(bool)\n",
    "\n",
    "normal_train_data = train_data[train_labels]\n",
    "normal_test_data = test_data[test_labels]\n",
    "\n",
    "anomalous_train_data = train_data[~train_labels]\n",
    "anomalous_test_data = test_data[~test_labels]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wVcTBDo-CqFS"
   },
   "source": [
    "Plot a normal ECG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.123037Z",
     "iopub.status.busy": "2024-07-19T01:35:56.122808Z",
     "iopub.status.idle": "2024-07-19T01:35:56.244732Z",
     "shell.execute_reply": "2024-07-19T01:35:56.244140Z"
    },
    "id": "ZTlMIrpmseYe"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.plot(np.arange(140), normal_train_data[0])\n",
    "plt.title(\"A Normal ECG\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QpI9by2ZA0NN"
   },
   "source": [
    "Plot an anomalous ECG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.247970Z",
     "iopub.status.busy": "2024-07-19T01:35:56.247749Z",
     "iopub.status.idle": "2024-07-19T01:35:56.354889Z",
     "shell.execute_reply": "2024-07-19T01:35:56.354268Z"
    },
    "id": "zrpXREF2siBr"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.plot(np.arange(140), anomalous_train_data[0])\n",
    "plt.title(\"An Anomalous ECG\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0DS6QKZJslZz"
   },
   "source": [
    "### Build the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.358104Z",
     "iopub.status.busy": "2024-07-19T01:35:56.357871Z",
     "iopub.status.idle": "2024-07-19T01:35:56.368500Z",
     "shell.execute_reply": "2024-07-19T01:35:56.367895Z"
    },
    "id": "bf6owZQDsp9y"
   },
   "outputs": [],
   "source": [
    "class AnomalyDetector(Model):\n",
    "  def __init__(self):\n",
    "    super(AnomalyDetector, self).__init__()\n",
    "    self.encoder = tf.keras.Sequential([\n",
    "      layers.Dense(32, activation=\"relu\"),\n",
    "      layers.Dense(16, activation=\"relu\"),\n",
    "      layers.Dense(8, activation=\"relu\")])\n",
    "\n",
    "    self.decoder = tf.keras.Sequential([\n",
    "      layers.Dense(16, activation=\"relu\"),\n",
    "      layers.Dense(32, activation=\"relu\"),\n",
    "      layers.Dense(140, activation=\"sigmoid\")])\n",
    "\n",
    "  def call(self, x):\n",
    "    encoded = self.encoder(x)\n",
    "    decoded = self.decoder(encoded)\n",
    "    return decoded\n",
    "\n",
    "autoencoder = AnomalyDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.371390Z",
     "iopub.status.busy": "2024-07-19T01:35:56.371171Z",
     "iopub.status.idle": "2024-07-19T01:35:56.377567Z",
     "shell.execute_reply": "2024-07-19T01:35:56.376959Z"
    },
    "id": "gwRpBBbg463S"
   },
   "outputs": [],
   "source": [
    "autoencoder.compile(optimizer='adam', loss='mae')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zuTy60STBEy4"
   },
   "source": [
    "Notice that the autoencoder is trained using only the normal ECGs, but is evaluated using the full test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:35:56.381133Z",
     "iopub.status.busy": "2024-07-19T01:35:56.380661Z",
     "iopub.status.idle": "2024-07-19T01:36:03.063149Z",
     "shell.execute_reply": "2024-07-19T01:36:03.062482Z"
    },
    "id": "V6NFSs-jsty2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m11s\u001b[0m 3s/step - loss: 0.0621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 325ms/step - loss: 0.0605"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 503ms/step - loss: 0.0604 - val_loss: 0.0539\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 45ms/step - loss: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0573 - val_loss: 0.0528\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0559 - val_loss: 0.0516\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0549"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0544 - val_loss: 0.0503\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0529"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0522 - val_loss: 0.0486\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 41ms/step - loss: 0.0495"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0488 - val_loss: 0.0470\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0457"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0446 - val_loss: 0.0454\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0413"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0407 - val_loss: 0.0433\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0380"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0373 - val_loss: 0.0417\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0344 - val_loss: 0.0410\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0325"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0321 - val_loss: 0.0397\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0303"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0302 - val_loss: 0.0389\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 41ms/step - loss: 0.0290"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0287 - val_loss: 0.0381\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 43ms/step - loss: 0.0280"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0275 - val_loss: 0.0372\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0267"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - loss: 0.0264 - val_loss: 0.0366\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 41ms/step - loss: 0.0262"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0256 - val_loss: 0.0358\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0251"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0249 - val_loss: 0.0353\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0244"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0243 - val_loss: 0.0348\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0238"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0236 - val_loss: 0.0344\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0226"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0228 - val_loss: 0.0340\n"
     ]
    }
   ],
   "source": [
    "history = autoencoder.fit(normal_train_data, normal_train_data,\n",
    "          epochs=20,\n",
    "          batch_size=512,\n",
    "          validation_data=(test_data, test_data),\n",
    "          shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:03.066498Z",
     "iopub.status.busy": "2024-07-19T01:36:03.066239Z",
     "iopub.status.idle": "2024-07-19T01:36:03.215658Z",
     "shell.execute_reply": "2024-07-19T01:36:03.214984Z"
    },
    "id": "OEexphFwwTQS"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc016981f10>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history[\"loss\"], label=\"Training Loss\")\n",
    "plt.plot(history.history[\"val_loss\"], label=\"Validation Loss\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ceI5lKv1BT-A"
   },
   "source": [
    "You will soon classify an ECG as anomalous if the reconstruction error is greater than one standard deviation from the normal training examples. First, let's plot a normal ECG from the training set, the reconstruction after it's encoded and decoded by the autoencoder, and the reconstruction error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:03.218754Z",
     "iopub.status.busy": "2024-07-19T01:36:03.218520Z",
     "iopub.status.idle": "2024-07-19T01:36:03.354534Z",
     "shell.execute_reply": "2024-07-19T01:36:03.353697Z"
    },
    "id": "hmsk4DuktxJ2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "encoded_data = autoencoder.encoder(normal_test_data).numpy()\n",
    "decoded_data = autoencoder.decoder(encoded_data).numpy()\n",
    "\n",
    "plt.plot(normal_test_data[0], 'b')\n",
    "plt.plot(decoded_data[0], 'r')\n",
    "plt.fill_between(np.arange(140), decoded_data[0], normal_test_data[0], color='lightcoral')\n",
    "plt.legend(labels=[\"Input\", \"Reconstruction\", \"Error\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ocA_q9ufB_aF"
   },
   "source": [
    "Create a similar plot, this time for an anomalous test example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:03.358070Z",
     "iopub.status.busy": "2024-07-19T01:36:03.357802Z",
     "iopub.status.idle": "2024-07-19T01:36:03.499541Z",
     "shell.execute_reply": "2024-07-19T01:36:03.498785Z"
    },
    "id": "vNFTuPhLwTBn"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "encoded_data = autoencoder.encoder(anomalous_test_data).numpy()\n",
    "decoded_data = autoencoder.decoder(encoded_data).numpy()\n",
    "\n",
    "plt.plot(anomalous_test_data[0], 'b')\n",
    "plt.plot(decoded_data[0], 'r')\n",
    "plt.fill_between(np.arange(140), decoded_data[0], anomalous_test_data[0], color='lightcoral')\n",
    "plt.legend(labels=[\"Input\", \"Reconstruction\", \"Error\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ocimg3MBswdS"
   },
   "source": [
    "### Detect anomalies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Xnh8wmkDsypN"
   },
   "source": [
    "Detect anomalies by calculating whether the reconstruction loss is greater than a fixed threshold. In this tutorial, you will calculate the mean average error for normal examples from the training set, then classify future examples as anomalous if the reconstruction error is higher than one standard deviation from the training set.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TeuT8uTA5Y_w"
   },
   "source": [
    "Plot the reconstruction error on normal ECGs from the training set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:03.503303Z",
     "iopub.status.busy": "2024-07-19T01:36:03.503062Z",
     "iopub.status.idle": "2024-07-19T01:36:04.543159Z",
     "shell.execute_reply": "2024-07-19T01:36:04.542518Z"
    },
    "id": "N7FltOnHu4-l"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m 1/74\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m30s\u001b[0m 421ms/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m46/74\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m74/74\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m74/74\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reconstructions = autoencoder.predict(normal_train_data)\n",
    "train_loss = tf.keras.losses.mae(reconstructions, normal_train_data)\n",
    "\n",
    "plt.hist(train_loss[None,:], bins=50)\n",
    "plt.xlabel(\"Train loss\")\n",
    "plt.ylabel(\"No of examples\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mh-3ChEF5hog"
   },
   "source": [
    "Choose a threshold value that is one standard deviations above the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:04.546519Z",
     "iopub.status.busy": "2024-07-19T01:36:04.546284Z",
     "iopub.status.idle": "2024-07-19T01:36:04.550550Z",
     "shell.execute_reply": "2024-07-19T01:36:04.549828Z"
    },
    "id": "82hkl0Chs3P_"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Threshold:  0.034314327\n"
     ]
    }
   ],
   "source": [
    "threshold = np.mean(train_loss) + np.std(train_loss)\n",
    "print(\"Threshold: \", threshold)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uEGlA1Be50Nj"
   },
   "source": [
    "Note: There are other strategies you could use to select a threshold value above which test examples should be classified as anomalous, the correct approach will depend on your dataset. You can learn more with the links at the end of this tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zpLSDAeb51D_"
   },
   "source": [
    "If you examine the reconstruction error for the anomalous examples in the test set, you'll notice most have greater reconstruction error than the threshold. By varing the threshold, you can adjust the [precision](https://developers.google.com/machine-learning/glossary#precision) and [recall](https://developers.google.com/machine-learning/glossary#recall) of your classifier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:04.553832Z",
     "iopub.status.busy": "2024-07-19T01:36:04.553587Z",
     "iopub.status.idle": "2024-07-19T01:36:05.084676Z",
     "shell.execute_reply": "2024-07-19T01:36:05.084018Z"
    },
    "id": "sKVwjQK955Wy"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "\u001b[1m 1/14\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 39ms/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m14/14\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "\u001b[1m14/14\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reconstructions = autoencoder.predict(anomalous_test_data)\n",
    "test_loss = tf.keras.losses.mae(reconstructions, anomalous_test_data)\n",
    "\n",
    "plt.hist(test_loss[None, :], bins=50)\n",
    "plt.xlabel(\"Test loss\")\n",
    "plt.ylabel(\"No of examples\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PFVk_XGE6AX2"
   },
   "source": [
    "Classify an ECG as an anomaly if the reconstruction error is greater than the threshold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:05.088058Z",
     "iopub.status.busy": "2024-07-19T01:36:05.087804Z",
     "iopub.status.idle": "2024-07-19T01:36:05.092308Z",
     "shell.execute_reply": "2024-07-19T01:36:05.091723Z"
    },
    "id": "mkgJZfhh6CHr"
   },
   "outputs": [],
   "source": [
    "def predict(model, data, threshold):\n",
    "  reconstructions = model(data)\n",
    "  loss = tf.keras.losses.mae(reconstructions, data)\n",
    "  return tf.math.less(loss, threshold)\n",
    "\n",
    "def print_stats(predictions, labels):\n",
    "  print(\"Accuracy = {}\".format(accuracy_score(labels, predictions)))\n",
    "  print(\"Precision = {}\".format(precision_score(labels, predictions)))\n",
    "  print(\"Recall = {}\".format(recall_score(labels, predictions)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-19T01:36:05.095186Z",
     "iopub.status.busy": "2024-07-19T01:36:05.094952Z",
     "iopub.status.idle": "2024-07-19T01:36:05.112816Z",
     "shell.execute_reply": "2024-07-19T01:36:05.112173Z"
    },
    "id": "sOcfXfXq6FBd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy = 0.943\n",
      "Precision = 0.9921722113502935\n",
      "Recall = 0.9053571428571429\n"
     ]
    }
   ],
   "source": [
    "preds = predict(autoencoder, test_data, threshold)\n",
    "print_stats(preds, test_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HrJRef8Ln945"
   },
   "source": [
    "## Next steps\n",
    "\n",
    "To learn more about anomaly detection with autoencoders, check out this excellent [interactive example](https://anomagram.fastforwardlabs.com/#/) built with TensorFlow.js by Victor Dibia. For a real-world use case, you can learn how [Airbus Detects Anomalies in ISS Telemetry Data](https://blog.tensorflow.org/2020/04/how-airbus-detects-anomalies-iss-telemetry-data-tfx.html) using TensorFlow. To learn more about the basics, consider reading this [blog post](https://blog.keras.io/building-autoencoders-in-keras.html) by François Chollet. For more details, check out chapter 14 from [Deep Learning](https://www.deeplearningbook.org/) by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.\n"
   ]
  }
 ],
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  "accelerator": "GPU",
  "colab": {
   "gpuType": "T4",
   "private_outputs": true,
   "provenance": [
    {
     "file_id": "17gKB2bKebV2DzoYIMFzyEXA5uDnwWOvT",
     "timestamp": 1712793165979
    },
    {
     "file_id": "https://github.com/tensorflow/docs/blob/master/site/en/tutorials/generative/autoencoder.ipynb",
     "timestamp": 1712792176273
    }
   ],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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