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{
"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": "2024-08-16T05:08:23.508239Z",
"iopub.status.busy": "2024-08-16T05:08:23.507994Z",
"iopub.status.idle": "2024-08-16T05:08:23.511970Z",
"shell.execute_reply": "2024-08-16T05:08:23.511344Z"
},
"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": [
"\n",
"
"
]
},
{
"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": "2024-08-16T05:08:23.516087Z",
"iopub.status.busy": "2024-08-16T05:08:23.515550Z",
"iopub.status.idle": "2024-08-16T05:08:26.461467Z",
"shell.execute_reply": "2024-08-16T05:08:26.460737Z"
},
"id": "YfIk2es3hJEd"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024-08-16 05:08:24.454969: 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",
"2024-08-16 05:08:24.475836: 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",
"2024-08-16 05:08:24.482184: 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": "2024-08-16T05:08:26.465909Z",
"iopub.status.busy": "2024-08-16T05:08:26.465480Z",
"iopub.status.idle": "2024-08-16T05:08:26.951978Z",
"shell.execute_reply": "2024-08-16T05:08:26.951144Z"
},
"id": "YZm503-I_tji"
},
"outputs": [
{
"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",
"\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": "2024-08-16T05:08:26.955535Z",
"iopub.status.busy": "2024-08-16T05:08:26.955262Z",
"iopub.status.idle": "2024-08-16T05:08:29.196992Z",
"shell.execute_reply": "2024-08-16T05:08:29.196168Z"
},
"id": "0MUxidpyChjX"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
"I0000 00:00:1723784907.495092 160375 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 00:00:1723784907.498985 160375 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 00:00:1723784907.502627 160375 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 00:00:1723784907.506226 160375 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 00:00:1723784907.518853 160375 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 00:00:1723784907.522303 160375 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 00:00:1723784907.525756 160375 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 00:00:1723784907.529169 160375 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 00:00:1723784907.532506 160375 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 00:00:1723784907.536023 160375 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 00:00:1723784907.539501 160375 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 00:00:1723784907.542895 160375 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 00:00:1723784908.772373 160375 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 00:00:1723784908.774589 160375 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 00:00:1723784908.776554 160375 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 00:00:1723784908.778641 160375 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 00:00:1723784908.780679 160375 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 00:00:1723784908.782717 160375 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 00:00:1723784908.784577 160375 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 00:00:1723784908.786661 160375 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 00:00:1723784908.788966 160375 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 00:00:1723784908.791004 160375 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 00:00:1723784908.792858 160375 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 00:00:1723784908.795056 160375 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 00:00:1723784908.833540 160375 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 00:00:1723784908.835672 160375 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 00:00:1723784908.837578 160375 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 00:00:1723784908.839614 160375 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 00:00:1723784908.841487 160375 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 00:00:1723784908.843549 160375 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 00:00:1723784908.845399 160375 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 00:00:1723784908.847401 160375 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 00:00:1723784908.849242 160375 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 00:00:1723784908.851783 160375 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 00:00:1723784908.854229 160375 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 00:00:1723784908.856641 160375 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": "2024-08-16T05:08:29.200930Z",
"iopub.status.busy": "2024-08-16T05:08:29.200574Z",
"iopub.status.idle": "2024-08-16T05:08:29.216831Z",
"shell.execute_reply": "2024-08-16T05:08:29.216260Z"
},
"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": "2024-08-16T05:08:29.220373Z",
"iopub.status.busy": "2024-08-16T05:08:29.219777Z",
"iopub.status.idle": "2024-08-16T05:08:56.658179Z",
"shell.execute_reply": "2024-08-16T05:08:56.657521Z"
},
"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 00:00:1723784911.543932 160540 service.cc:146] XLA service 0x7f8910006f20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
"I0000 00:00:1723784911.543965 160540 service.cc:154] StreamExecutor device (0): Tesla T4, Compute Capability 7.5\n",
"I0000 00:00:1723784911.543969 160540 service.cc:154] StreamExecutor device (1): Tesla T4, Compute Capability 7.5\n",
"I0000 00:00:1723784911.543973 160540 service.cc:154] StreamExecutor device (2): Tesla T4, Compute Capability 7.5\n",
"I0000 00:00:1723784911.543976 160540 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[1m1:03:55\u001b[0m 2s/step - loss: 0.1735"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 43/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.1347 "
]
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 90/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.1133"
]
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{
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 137/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1008"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"I0000 00:00:1723784912.197500 160540 device_compiler.h:188] Compiled cluster using XLA! This line is logged at most once for the lifetime of the process.\n"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0925"
]
},
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"output_type": "stream",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 229/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0863"
]
},
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 276/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0812"
]
},
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 323/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0771"
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 369/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0737"
]
},
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"output_type": "stream",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 415/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0708"
]
},
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"output_type": "stream",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 462/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0682"
]
},
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"output_type": "stream",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 509/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0659"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 556/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0639"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 602/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0621"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0604"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 695/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0590"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0576"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 789/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0563"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 836/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0551"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 1ms/step - loss: 0.0540"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0531"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m0s\u001b[0m 1ms/step - loss: 0.0522"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0513"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1055/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0504"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m0s\u001b[0m 1ms/step - loss: 0.0496"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1147/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0489"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1193/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0481"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1239/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0474"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1284/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0468"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0462"
]
},
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1372/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0456"
]
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"output_type": "stream",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1417/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0450"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0444"
]
},
{
"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[1m1507/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0439"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1553/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0434"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 1ms/step - loss: 0.0429"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1643/1875\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[1m1688/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0420"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1732/1875\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[1m1777/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0411"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1822/1875\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[1m1868/1875\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[1m5s\u001b[0m 2ms/step - loss: 0.0402 - val_loss: 0.0134\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[1m1:25\u001b[0m 46ms/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\b\b\b\r",
"\u001b[1m 46/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\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 95/1875\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 143/1875\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 192/1875\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 240/1875\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 289/1875\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 338/1875\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 387/1875\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 434/1875\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 482/1875\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 531/1875\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 580/1875\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 629/1875\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 677/1875\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 726/1875\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 774/1875\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 822/1875\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 871/1875\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 920/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m0s\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 967/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1013/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1060/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1109/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1158/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1207/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1256/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\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[1m1306/1875\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[1m1354/1875\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[1m1402/1875\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[1m1452/1875\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[1m1501/1875\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[1m1551/1875\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[1m1600/1875\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[1m1649/1875\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[1m1697/1875\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[1m1746/1875\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[1m1793/1875\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[1m1841/1875\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0124 - 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[1m1:26\u001b[0m 46ms/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\b\b\b\r",
"\u001b[1m 47/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/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 94/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 141/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 187/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 235/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 282/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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[1m 328/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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[1m 375/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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[1m 422/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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[1m 470/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 613/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 660/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 755/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 803/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0106"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0105"
]
},
{
"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\r",
"\u001b[1m 899/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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\r",
"\u001b[1m 947/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m 995/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1043/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1090/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1138/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1186/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1233/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1281/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1330/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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\r",
"\u001b[1m1378/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1427/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1476/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1524/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1570/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1616/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1663/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1710/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1757/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1804/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1852/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0104 - val_loss: 0.0098\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[1m1:25\u001b[0m 46ms/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\b\b\b\r",
"\u001b[1m 46/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0099 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0099"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0099"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 189/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0099"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 1ms/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 283/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 331/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 379/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 426/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 473/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 521/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 570/1875\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 618/1875\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 667/1875\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 714/1875\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 762/1875\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 810/1875\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 858/1875\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 906/1875\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 953/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1001/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1049/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1097/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1144/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0097"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1192/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1240/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0097"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1287/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\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[1m1336/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1384/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1432/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1480/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1528/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1575/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1622/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1670/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1718/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1766/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1814/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1861/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0097 - val_loss: 0.0095\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[1m1:26\u001b[0m 46ms/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\b\b\b\r",
"\u001b[1m 47/1875\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 94/1875\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 141/1875\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 188/1875\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 235/1875\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 282/1875\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 330/1875\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 377/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 423/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 470/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 516/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 564/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 612/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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[1m1s\u001b[0m 1ms/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 706/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 752/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 799/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 845/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 892/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 939/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/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 987/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1035/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1083/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1132/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1180/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1229/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1277/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1324/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1371/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1419/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1467/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1515/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1563/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1610/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1657/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1704/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1752/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1800/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m1847/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 1ms/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[1m2s\u001b[0m 1ms/step - loss: 0.0093 - val_loss: 0.0092\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: 0.0075"
]
},
{
"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: 0.0090 "
]
},
{
"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 91/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\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 135/1875\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 181/1875\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 228/1875\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 275/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.0092"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 322/1875\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 370/1875\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 416/1875\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 461/1875\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 506/1875\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 552/1875\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 598/1875\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 645/1875\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 693/1875\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 739/1875\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 787/1875\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 834/1875\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 880/1875\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 925/1875\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 971/1875\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[1m1015/1875\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[1m1060/1875\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[1m1105/1875\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[1m1149/1875\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[1m1194/1875\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[1m1241/1875\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[1m1286/1875\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[1m1332/1875\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[1m1378/1875\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[1m1423/1875\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[1m1469/1875\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[1m1515/1875\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[1m1561/1875\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[1m1606/1875\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[1m1652/1875\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[1m1698/1875\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[1m1745/1875\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[1m1793/1875\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[1m1840/1875\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: 0.0091\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[1m1:23\u001b[0m 45ms/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 47/1875\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 94/1875\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 141/1875\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 188/1875\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 237/1875\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 286/1875\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 334/1875\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 380/1875\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 427/1875\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 475/1875\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 523/1875\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 571/1875\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 618/1875\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 665/1875\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 712/1875\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 805/1875\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 852/1875\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 899/1875\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 946/1875\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[1m 993/1875\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[1m1040/1875\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[1m1087/1875\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[1m1134/1875\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[1m1181/1875\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[1m1228/1875\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[1m1275/1875\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[1m1322/1875\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[1m1369/1875\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[1m1417/1875\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[1m1464/1875\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[1m1512/1875\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[1m1559/1875\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[1m1605/1875\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[1m1651/1875\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[1m1698/1875\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[1m1745/1875\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[1m1792/1875\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[1m1838/1875\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 8/10\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: 0.0090"
]
},
{
"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\b\b\b\r",
"\u001b[1m 48/1875\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 96/1875\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 144/1875\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 191/1875\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 240/1875\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 287/1875\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 336/1875\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 385/1875\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 434/1875\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 482/1875\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 530/1875\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 578/1875\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 626/1875\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 673/1875\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 720/1875\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 768/1875\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 817/1875\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 866/1875\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 914/1875\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 962/1875\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[1m1010/1875\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[1m1058/1875\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[1m1105/1875\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[1m1154/1875\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[1m1202/1875\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[1m1248/1875\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[1m1296/1875\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[1m1344/1875\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[1m1392/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1440/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1489/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1537/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1586/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1634/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1681/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1729/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1777/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1826/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1874/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0089 - 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[1m1:24\u001b[0m 45ms/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 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 94/1875\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 141/1875\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 188/1875\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 235/1875\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 282/1875\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 329/1875\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 375/1875\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 421/1875\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 468/1875\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 516/1875\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 564/1875\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 613/1875\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 661/1875\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 709/1875\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 757/1875\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 805/1875\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 853/1875\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 901/1875\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 949/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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 997/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1045/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1092/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1138/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1185/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\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[1m1232/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\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[1m1279/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\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[1m1327/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1375/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1424/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1473/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1522/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1570/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1618/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1666/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1714/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1763/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1812/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1860/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 1ms/step - loss: 0.0089 - val_loss: 0.0089\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[1m1:25\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 47/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\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 96/1875\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 145/1875\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 194/1875\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 243/1875\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 291/1875\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 338/1875\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 385/1875\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 432/1875\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 479/1875\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 525/1875\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 572/1875\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 619/1875\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 668/1875\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 717/1875\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 767/1875\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 816/1875\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 865/1875\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 914/1875\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 960/1875\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[1m1006/1875\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[1m1052/1875\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[1m1098/1875\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[1m1145/1875\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[1m1193/1875\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[1m1241/1875\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[1m1289/1875\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[1m1336/1875\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[1m1382/1875\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[1m1429/1875\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[1m1475/1875\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[1m1522/1875\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[1m1568/1875\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[1m1614/1875\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[1m1660/1875\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[1m1706/1875\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[1m1753/1875\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[1m1799/1875\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[1m1845/1875\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"
]
},
{
"data": {
"text/plain": [
""
]
},
"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": "2024-08-16T05:08:56.661491Z",
"iopub.status.busy": "2024-08-16T05:08:56.661241Z",
"iopub.status.idle": "2024-08-16T05:08:56.830984Z",
"shell.execute_reply": "2024-08-16T05:08:56.830252Z"
},
"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": "2024-08-16T05:08:56.835301Z",
"iopub.status.busy": "2024-08-16T05:08:56.834660Z",
"iopub.status.idle": "2024-08-16T05:08:57.272919Z",
"shell.execute_reply": "2024-08-16T05:08:57.272284Z"
},
"id": "s4LlDOS6FUA1"
},
"outputs": [
{
"data": {
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"text/plain": [
"
\n",
" \n",
" ![](\"https://www.tensorflow.org/images/tf_logo_32px.png\"){kind=logo} \n",
" View on TensorFlow.org\n",
" | \n",
" \n",
" \n",
" ![](\"https://www.tensorflow.org/images/colab_logo_32px.png\"){kind=logo} \n",
" Run in Google Colab\n",
" | \n",
" \n",
" \n",
" ![](\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\") \n",
" View source on GitHub\n",
" | \n",
" \n",
" ![](\"https://www.tensorflow.org/images/download_logo_32px.png\"){kind=logo} Download notebook\n",
" | \n",
"
"
]
},
"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",
"\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": "2024-08-16T05:08:57.276905Z",
"iopub.status.busy": "2024-08-16T05:08:57.276501Z",
"iopub.status.idle": "2024-08-16T05:08:57.631164Z",
"shell.execute_reply": "2024-08-16T05:08:57.630455Z"
},
"id": "gDYHJA2PCQ3m"
},
"outputs": [],
"source": [
"(x_train, _), (x_test, _) = fashion_mnist.load_data()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-16T05:08:57.635346Z",
"iopub.status.busy": "2024-08-16T05:08:57.634768Z",
"iopub.status.idle": "2024-08-16T05:08:57.724216Z",
"shell.execute_reply": "2024-08-16T05:08:57.723450Z"
},
"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": "2024-08-16T05:08:57.727602Z",
"iopub.status.busy": "2024-08-16T05:08:57.727346Z",
"iopub.status.idle": "2024-08-16T05:08:58.694844Z",
"shell.execute_reply": "2024-08-16T05:08:58.693947Z"
},
"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": "2024-08-16T05:08:58.699206Z",
"iopub.status.busy": "2024-08-16T05:08:58.698575Z",
"iopub.status.idle": "2024-08-16T05:08:59.347039Z",
"shell.execute_reply": "2024-08-16T05:08:59.346397Z"
},
"id": "thKUmbVVCQpt"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"
"
]
},
"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": "2024-08-16T05:08:59.350671Z",
"iopub.status.busy": "2024-08-16T05:08:59.350427Z",
"iopub.status.idle": "2024-08-16T05:08:59.378767Z",
"shell.execute_reply": "2024-08-16T05:08:59.378096Z"
},
"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": "2024-08-16T05:08:59.381995Z",
"iopub.status.busy": "2024-08-16T05:08:59.381461Z",
"iopub.status.idle": "2024-08-16T05:08:59.387699Z",
"shell.execute_reply": "2024-08-16T05:08:59.387125Z"
},
"id": "QYKbiDFYCQfj"
},
"outputs": [],
"source": [
"autoencoder.compile(optimizer='adam', loss=losses.MeanSquaredError())"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-16T05:08:59.390711Z",
"iopub.status.busy": "2024-08-16T05:08:59.390349Z",
"iopub.status.idle": "2024-08-16T05:09:40.702609Z",
"shell.execute_reply": "2024-08-16T05:09:40.701794Z"
},
"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[1m1:28:19\u001b[0m 3s/step - loss: 0.1770"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1660 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 61/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.1559"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.1416"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 126/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1284"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.1175"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 189/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1088"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 221/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.1013"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 253/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0950"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 285/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0896"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0850"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 350/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0808"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 382/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0773"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 415/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0741"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 446/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0713"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 479/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0687"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 512/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0664"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0642"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 578/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0622"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0604"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0588"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0572"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 713/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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 747/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0543"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0530"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0519"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0507"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0497"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0487"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0479"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 979/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0470"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0462"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0454"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/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[1m1110/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0440"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1143/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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[1m1175/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0427"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1208/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0420"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m0s\u001b[0m 2ms/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[1m1274/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0409"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1308/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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[1m1341/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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[1m1375/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0393"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0388"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/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[1m1474/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0379"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0374"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0370"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0366"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0362"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1634/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0355"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0352"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0348"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1763/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0345"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0342"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1828/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0339"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1860/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0336"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0334 - val_loss: 0.0095\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[1m1:29\u001b[0m 48ms/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 29/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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 57/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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 86/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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 116/1875\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 147/1875\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 176/1875\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 205/1875\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 234/1875\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 263/1875\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 291/1875\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 320/1875\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 349/1875\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 378/1875\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 436/1875\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 465/1875\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 494/1875\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 523/1875\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 551/1875\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 580/1875\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 609/1875\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 639/1875\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 667/1875\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 696/1875\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 724/1875\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 753/1875\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 782/1875\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 810/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 839/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 868/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 896/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 924/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 952/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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 980/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1008/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1036/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1064/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0092"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1092/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1120/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1148/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0092"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1176/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0092"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1204/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1232/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1260/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1288/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1316/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1343/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1371/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1399/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1427/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1455/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1483/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1511/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1539/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1566/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1594/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1622/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1650/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1679/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1708/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1737/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1766/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1794/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1822/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1850/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0091 - val_loss: 0.0083\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[1m1:28\u001b[0m 47ms/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 28/1875\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 55/1875\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 82/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 109/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 136/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 164/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 192/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 220/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 248/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 276/1875\u001b[0m \u001b[32m━━\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 303/1875\u001b[0m \u001b[32m━━━\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 331/1875\u001b[0m \u001b[32m━━━\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 359/1875\u001b[0m \u001b[32m━━━\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 387/1875\u001b[0m \u001b[32m━━━━\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 414/1875\u001b[0m \u001b[32m━━━━\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 441/1875\u001b[0m \u001b[32m━━━━\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 468/1875\u001b[0m \u001b[32m━━━━\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 495/1875\u001b[0m \u001b[32m━━━━━\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 523/1875\u001b[0m \u001b[32m━━━━━\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 551/1875\u001b[0m \u001b[32m━━━━━\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 579/1875\u001b[0m \u001b[32m━━━━━━\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 606/1875\u001b[0m \u001b[32m━━━━━━\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 634/1875\u001b[0m \u001b[32m━━━━━━\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 661/1875\u001b[0m \u001b[32m━━━━━━━\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 688/1875\u001b[0m \u001b[32m━━━━━━━\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 716/1875\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 744/1875\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 772/1875\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 800/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 827/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 855/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 883/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 911/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\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 939/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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 967/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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 995/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1022/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1050/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1078/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1106/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1134/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1161/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1189/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1217/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\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[1m1245/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1273/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1301/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\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[1m1328/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\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[1m1356/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1384/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\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[1m1411/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1438/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1465/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1492/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\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[1m1518/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1545/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1571/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\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[1m1597/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1624/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1651/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1678/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\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[1m1705/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1732/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1759/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\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[1m1786/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1813/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1840/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1867/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\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[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0082 - val_loss: 0.0078\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: 0.0078"
]
},
{
"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\b\b\b\r",
"\u001b[1m 27/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 53/1875\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 78/1875\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 104/1875\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 130/1875\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 156/1875\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 182/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 207/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 233/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 259/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 285/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 311/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 337/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\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 389/1875\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 415/1875\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 442/1875\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 468/1875\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 494/1875\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 520/1875\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 546/1875\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 572/1875\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 598/1875\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 624/1875\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 651/1875\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 678/1875\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 706/1875\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 733/1875\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 760/1875\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 787/1875\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 814/1875\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 841/1875\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 868/1875\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 895/1875\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 922/1875\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 950/1875\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 978/1875\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[1m1005/1875\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[1m1033/1875\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[1m1060/1875\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[1m1088/1875\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[1m1116/1875\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[1m1144/1875\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[1m1172/1875\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[1m1199/1875\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[1m1227/1875\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[1m1255/1875\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[1m1283/1875\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[1m1311/1875\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[1m1339/1875\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[1m1367/1875\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[1m1395/1875\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[1m1423/1875\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[1m1451/1875\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[1m1479/1875\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[1m1506/1875\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[1m1534/1875\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[1m1561/1875\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[1m1588/1875\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[1m1616/1875\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[1m1644/1875\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[1m1672/1875\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[1m1700/1875\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[1m1728/1875\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[1m1756/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1838/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1866/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0077 - val_loss: 0.0076\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[1m1:28\u001b[0m 47ms/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 29/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0076 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0075"
]
},
{
"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\r",
"\u001b[1m 86/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 114/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 142/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 171/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 200/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 229/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 258/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 287/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 316/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 345/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 374/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 403/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 432/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 461/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 490/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 519/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 548/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 577/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 606/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 635/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 664/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 694/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 723/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 752/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 781/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 810/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 839/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 868/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 897/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 926/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 955/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 984/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1013/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1042/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1071/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1100/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1129/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1158/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1187/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1216/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1245/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1274/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1303/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m1332/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1361/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1390/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1419/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1448/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1477/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1506/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1535/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1564/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1594/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1624/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1653/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1682/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1710/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1739/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1768/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1797/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1826/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1855/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/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\r",
"\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0075 - val_loss: 0.0074\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: 0.0076"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m3s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 118/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 147/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 177/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 206/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 420/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 450/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 481/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 544/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 606/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 670/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 733/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 764/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 827/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 859/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 891/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 954/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1050/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1113/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1145/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1176/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1207/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1239/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1335/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1397/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1428/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1491/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1553/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1648/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1680/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1711/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1773/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1837/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073 - val_loss: 0.0073\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[1m1:24\u001b[0m 45ms/step - loss: 0.0066"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m3s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 117/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m3s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 175/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 203/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 231/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 260/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 289/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 318/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 347/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 405/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 434/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 462/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 520/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 549/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 578/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 665/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 694/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 779/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 808/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 837/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 866/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 924/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1041/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1100/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1216/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1274/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1333/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1420/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1448/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1477/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1596/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1654/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1741/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1771/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1801/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1831/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1861/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 - val_loss: 0.0072\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[1m1:27\u001b[0m 47ms/step - loss: 0.0067"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 87/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 116/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0073"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m3s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 176/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 205/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 263/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 293/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 322/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 350/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 436/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 465/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 494/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 553/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 583/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 612/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 641/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 670/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 757/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 786/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 843/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 900/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 929/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 957/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1016/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1045/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1132/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1161/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1190/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1308/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1337/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1367/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1396/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1425/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1454/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1483/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1512/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1541/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1599/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1657/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1716/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1745/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1804/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1862/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071 - val_loss: 0.0071\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[1m1:25\u001b[0m 46ms/step - loss: 0.0072"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0072 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m3s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 117/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 147/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 177/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 267/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 297/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 357/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 387/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 417/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 447/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 507/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 624/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 683/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m2s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 772/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 802/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 831/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 891/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 921/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 950/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1100/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1160/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1221/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1280/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1341/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1371/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1402/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1433/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1495/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1525/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1587/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1617/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1647/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1676/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1705/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1734/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1763/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1792/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1850/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0071"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0071 - val_loss: 0.0070\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[1m1:25\u001b[0m 46ms/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: 0.0069 "
]
},
{
"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\r",
"\u001b[1m 59/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 88/1875\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - loss: 0.0068"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 117/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 146/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 2ms/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\r",
"\u001b[1m 175/1875\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 204/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 234/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 264/1875\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 294/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 323/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 352/1875\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 382/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 411/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 440/1875\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 469/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 499/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 528/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 557/1875\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 586/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 615/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 644/1875\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 675/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 705/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 2ms/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\r",
"\u001b[1m 734/1875\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 765/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 795/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 824/1875\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 853/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 883/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/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\r",
"\u001b[1m 912/1875\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 970/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 999/1875\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1058/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1087/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1116/1875\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1145/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1174/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1204/1875\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1235/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1265/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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[1m1s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1326/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1387/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
]
},
{
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"output_type": "stream",
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"\u001b[1m1449/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1480/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1511/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1541/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1572/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1603/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1634/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1665/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\u001b[1m1696/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0070"
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1756/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1785/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1814/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1843/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1872/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - loss: 0.0070"
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - loss: 0.0070 - val_loss: 0.0070\n"
]
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"data": {
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""
]
},
"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": "2024-08-16T05:09:40.706339Z",
"iopub.status.busy": "2024-08-16T05:09:40.705669Z",
"iopub.status.idle": "2024-08-16T05:09:40.718983Z",
"shell.execute_reply": "2024-08-16T05:09:40.718268Z"
},
"id": "oEpxlX6sTEQz"
},
"outputs": [
{
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Model: \"sequential_2\"\n",
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Trainable params: 1,320 (5.16 KB)\n", "\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": [ "
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Model: \"sequential_3\"\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\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": {
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measurement accuracy will be reduced\n", "W0000 00:00:1723784980.796207 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.799227 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.804537 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.809107 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.819083 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.834257 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.836833 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.839615 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.843009 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.846674 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.850582 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.856645 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.862215 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.867756 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.875814 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.883118 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.885883 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.888425 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.891329 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.894740 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.898476 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.936863 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.941096 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.944674 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.949005 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "W0000 00:00:1723784980.961848 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.966838 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.973690 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.980217 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784980.999480 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.013945 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.038542 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.056058 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.077900 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.099924 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.115882 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.137481 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "W0000 00:00:1723784981.186111 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.207864 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.329616 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.337779 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.352611 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.369650 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "W0000 00:00:1723784981.399198 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.413427 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.443673 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.502975 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.545023 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "W0000 00:00:1723784981.626188 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.642306 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.657118 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.675985 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.707544 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.718098 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.751437 160375 gpu_timer.cc:114] Skipping the delay kernel, measurement accuracy will be reduced\n", "W0000 00:00:1723784981.774578 160375 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": "2024-08-16T05:09:41.830952Z", "iopub.status.busy": "2024-08-16T05:09:41.830700Z", "iopub.status.idle": "2024-08-16T05:09:42.404449Z", "shell.execute_reply": "2024-08-16T05:09:42.403784Z" }, "id": "sfxr9NdBCP_x" }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
"
]
},
"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](https://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](https://www.timeseriesclassification.com/description.php?Dataset=ECG5000).\n"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-16T05:09:42.408208Z",
"iopub.status.busy": "2024-08-16T05:09:42.407921Z",
"iopub.status.idle": "2024-08-16T05:09:42.795830Z",
"shell.execute_reply": "2024-08-16T05:09:42.795151Z"
},
"id": "KmKRDJWgsFYa"
},
"outputs": [
{
"data": {
"text/html": [
""
]
},
"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": "2024-08-16T05:09:42.993975Z",
"iopub.status.busy": "2024-08-16T05:09:42.993439Z",
"iopub.status.idle": "2024-08-16T05:09:43.102433Z",
"shell.execute_reply": "2024-08-16T05:09:43.101784Z"
},
"id": "zrpXREF2siBr"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:43.105538Z",
"iopub.status.busy": "2024-08-16T05:09:43.105139Z",
"iopub.status.idle": "2024-08-16T05:09:43.115699Z",
"shell.execute_reply": "2024-08-16T05:09:43.115113Z"
},
"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": "2024-08-16T05:09:43.119002Z",
"iopub.status.busy": "2024-08-16T05:09:43.118401Z",
"iopub.status.idle": "2024-08-16T05:09:43.124837Z",
"shell.execute_reply": "2024-08-16T05:09:43.124256Z"
},
"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": "2024-08-16T05:09:43.128078Z",
"iopub.status.busy": "2024-08-16T05:09:43.127650Z",
"iopub.status.idle": "2024-08-16T05:09:50.219910Z",
"shell.execute_reply": "2024-08-16T05:09:50.219194Z"
},
"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: 0.0588"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 365ms/step - loss: 0.0581"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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 551ms/step - loss: 0.0581 - val_loss: 0.0531\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 44ms/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\r",
"\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0553 - val_loss: 0.0518\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: 0.0528"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0519 - val_loss: 0.0494\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 41ms/step - loss: 0.0490"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0480 - val_loss: 0.0475\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: 0.0449"
]
},
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"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0441 - val_loss: 0.0451\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/20\n"
]
},
{
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"\r",
"\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0413"
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"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0405 - val_loss: 0.0435\n"
]
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{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/20\n"
]
},
{
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"text": [
"\r",
"\u001b[1m1/5\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 42ms/step - loss: 0.0375"
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0374 - val_loss: 0.0415\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8/20\n"
]
},
{
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"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: 0.0353"
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0347 - val_loss: 0.0403\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/20\n"
]
},
{
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"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: 0.0323"
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},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0323 - val_loss: 0.0392\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 43ms/step - loss: 0.0308"
]
},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0303 - val_loss: 0.0380\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 43ms/step - loss: 0.0289"
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},
{
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"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - loss: 0.0286 - val_loss: 0.0373\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 43ms/step - loss: 0.0273"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0272 - val_loss: 0.0367\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 43ms/step - loss: 0.0258"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0258 - val_loss: 0.0359\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 45ms/step - loss: 0.0257"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0253 - val_loss: 0.0354\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 44ms/step - loss: 0.0247"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0244 - val_loss: 0.0349\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 44ms/step - loss: 0.0236"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0342\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 44ms/step - loss: 0.0228"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0336\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 44ms/step - loss: 0.0215"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0220 - val_loss: 0.0330\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 44ms/step - loss: 0.0211"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0215 - val_loss: 0.0326\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 45ms/step - loss: 0.0213"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\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: 0.0213 - val_loss: 0.0323\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": "2024-08-16T05:09:50.223542Z",
"iopub.status.busy": "2024-08-16T05:09:50.222859Z",
"iopub.status.idle": "2024-08-16T05:09:50.372600Z",
"shell.execute_reply": "2024-08-16T05:09:50.372011Z"
},
"id": "OEexphFwwTQS"
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:50.376353Z",
"iopub.status.busy": "2024-08-16T05:09:50.375857Z",
"iopub.status.idle": "2024-08-16T05:09:50.512876Z",
"shell.execute_reply": "2024-08-16T05:09:50.512258Z"
},
"id": "hmsk4DuktxJ2"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:50.516237Z",
"iopub.status.busy": "2024-08-16T05:09:50.515971Z",
"iopub.status.idle": "2024-08-16T05:09:50.644650Z",
"shell.execute_reply": "2024-08-16T05:09:50.644059Z"
},
"id": "vNFTuPhLwTBn"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:50.648521Z",
"iopub.status.busy": "2024-08-16T05:09:50.647842Z",
"iopub.status.idle": "2024-08-16T05:09:51.700226Z",
"shell.execute_reply": "2024-08-16T05:09:51.699544Z"
},
"id": "N7FltOnHu4-l"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/74\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m31s\u001b[0m 425ms/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[1m48/74\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 6ms/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 6ms/step\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:51.703569Z",
"iopub.status.busy": "2024-08-16T05:09:51.703303Z",
"iopub.status.idle": "2024-08-16T05:09:51.707434Z",
"shell.execute_reply": "2024-08-16T05:09:51.706820Z"
},
"id": "82hkl0Chs3P_"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Threshold: 0.032343477\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": "2024-08-16T05:09:51.711181Z",
"iopub.status.busy": "2024-08-16T05:09:51.710568Z",
"iopub.status.idle": "2024-08-16T05:09:52.188974Z",
"shell.execute_reply": "2024-08-16T05:09:52.188258Z"
},
"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 19ms/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 19ms/step\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"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": "2024-08-16T05:09:52.192466Z",
"iopub.status.busy": "2024-08-16T05:09:52.192176Z",
"iopub.status.idle": "2024-08-16T05:09:52.196762Z",
"shell.execute_reply": "2024-08-16T05:09:52.196153Z"
},
"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": "2024-08-16T05:09:52.200104Z",
"iopub.status.busy": "2024-08-16T05:09:52.199499Z",
"iopub.status.idle": "2024-08-16T05:09:52.217458Z",
"shell.execute_reply": "2024-08-16T05:09:52.216884Z"
},
"id": "sOcfXfXq6FBd"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.944\n",
"Precision = 0.9921875\n",
"Recall = 0.9071428571428571\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"
]
}
],
"metadata": {
"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"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.19"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
\n",
"\n",
"\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" 0 1 2 3 4 5 6 \\\n",
"0 -0.112522 -2.827204 -3.773897 -4.349751 -4.376041 -3.474986 -2.181408 \n",
"1 -1.100878 -3.996840 -4.285843 -4.506579 -4.022377 -3.234368 -1.566126 \n",
"2 -0.567088 -2.593450 -3.874230 -4.584095 -4.187449 -3.151462 -1.742940 \n",
"3 0.490473 -1.914407 -3.616364 -4.318823 -4.268016 -3.881110 -2.993280 \n",
"4 0.800232 -0.874252 -2.384761 -3.973292 -4.338224 -3.802422 -2.534510 \n",
"\n",
" 7 8 9 ... 131 132 133 134 \\\n",
"0 -1.818286 -1.250522 -0.477492 ... 0.792168 0.933541 0.796958 0.578621 \n",
"1 -0.992258 -0.754680 0.042321 ... 0.538356 0.656881 0.787490 0.724046 \n",
"2 -1.490659 -1.183580 -0.394229 ... 0.886073 0.531452 0.311377 -0.021919 \n",
"3 -1.671131 -1.333884 -0.965629 ... 0.350816 0.499111 0.600345 0.842069 \n",
"4 -1.783423 -1.594450 -0.753199 ... 1.148884 0.958434 1.059025 1.371682 \n",
"\n",
" 135 136 137 138 139 140 \n",
"0 0.257740 0.228077 0.123431 0.925286 0.193137 1.0 \n",
"1 0.555784 0.476333 0.773820 1.119621 -1.436250 1.0 \n",
"2 -0.713683 -0.532197 0.321097 0.904227 -0.421797 1.0 \n",
"3 0.952074 0.990133 1.086798 1.403011 -0.383564 1.0 \n",
"4 1.277392 0.960304 0.971020 1.614392 1.421456 1.0 \n",
"\n",
"[5 rows x 141 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Download the dataset\n",
"dataframe = pd.read_csv('https://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": "2024-08-16T05:09:42.799351Z",
"iopub.status.busy": "2024-08-16T05:09:42.798876Z",
"iopub.status.idle": "2024-08-16T05:09:42.806296Z",
"shell.execute_reply": "2024-08-16T05:09:42.805696Z"
},
"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": "2024-08-16T05:09:42.809727Z",
"iopub.status.busy": "2024-08-16T05:09:42.809284Z",
"iopub.status.idle": "2024-08-16T05:09:42.834425Z",
"shell.execute_reply": "2024-08-16T05:09:42.833790Z"
},
"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": "2024-08-16T05:09:42.837735Z",
"iopub.status.busy": "2024-08-16T05:09:42.837314Z",
"iopub.status.idle": "2024-08-16T05:09:42.865454Z",
"shell.execute_reply": "2024-08-16T05:09:42.864854Z"
},
"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": "2024-08-16T05:09:42.869047Z",
"iopub.status.busy": "2024-08-16T05:09:42.868563Z",
"iopub.status.idle": "2024-08-16T05:09:42.990789Z",
"shell.execute_reply": "2024-08-16T05:09:42.990187Z"
},
"id": "ZTlMIrpmseYe"
},
"outputs": [
{
"data": {
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"| \n", " | 0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "8 | \n", "9 | \n", "... | \n", "131 | \n", "132 | \n", "133 | \n", "134 | \n", "135 | \n", "136 | \n", "137 | \n", "138 | \n", "139 | \n", "140 | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "-0.112522 | \n", "-2.827204 | \n", "-3.773897 | \n", "-4.349751 | \n", "-4.376041 | \n", "-3.474986 | \n", "-2.181408 | \n", "-1.818286 | \n", "-1.250522 | \n", "-0.477492 | \n", "... | \n", "0.792168 | \n", "0.933541 | \n", "0.796958 | \n", "0.578621 | \n", "0.257740 | \n", "0.228077 | \n", "0.123431 | \n", "0.925286 | \n", "0.193137 | \n", "1.0 | \n", "
| 1 | \n", "-1.100878 | \n", "-3.996840 | \n", "-4.285843 | \n", "-4.506579 | \n", "-4.022377 | \n", "-3.234368 | \n", "-1.566126 | \n", "-0.992258 | \n", "-0.754680 | \n", "0.042321 | \n", "... | \n", "0.538356 | \n", "0.656881 | \n", "0.787490 | \n", "0.724046 | \n", "0.555784 | \n", "0.476333 | \n", "0.773820 | \n", "1.119621 | \n", "-1.436250 | \n", "1.0 | \n", "
| 2 | \n", "-0.567088 | \n", "-2.593450 | \n", "-3.874230 | \n", "-4.584095 | \n", "-4.187449 | \n", "-3.151462 | \n", "-1.742940 | \n", "-1.490659 | \n", "-1.183580 | \n", "-0.394229 | \n", "... | \n", "0.886073 | \n", "0.531452 | \n", "0.311377 | \n", "-0.021919 | \n", "-0.713683 | \n", "-0.532197 | \n", "0.321097 | \n", "0.904227 | \n", "-0.421797 | \n", "1.0 | \n", "
| 3 | \n", "0.490473 | \n", "-1.914407 | \n", "-3.616364 | \n", "-4.318823 | \n", "-4.268016 | \n", "-3.881110 | \n", "-2.993280 | \n", "-1.671131 | \n", "-1.333884 | \n", "-0.965629 | \n", "... | \n", "0.350816 | \n", "0.499111 | \n", "0.600345 | \n", "0.842069 | \n", "0.952074 | \n", "0.990133 | \n", "1.086798 | \n", "1.403011 | \n", "-0.383564 | \n", "1.0 | \n", "
| 4 | \n", "0.800232 | \n", "-0.874252 | \n", "-2.384761 | \n", "-3.973292 | \n", "-4.338224 | \n", "-3.802422 | \n", "-2.534510 | \n", "-1.783423 | \n", "-1.594450 | \n", "-0.753199 | \n", "... | \n", "1.148884 | \n", "0.958434 | \n", "1.059025 | \n", "1.371682 | \n", "1.277392 | \n", "0.960304 | \n", "0.971020 | \n", "1.614392 | \n", "1.421456 | \n", "1.0 | \n", "
5 rows × 141 columns
\n", "