test_resnet.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The tensorboard extension is already loaded. To reload it, use:\n",
      "  %reload_ext tensorboard\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "from tensorflow.python.ops import math_ops\n",
    "from common_models import ResNet34, ResNet50, ResNet152\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime, os\n",
    "plt.style.use('seaborn')\n",
    "%load_ext tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "(x_train, y_train), (x_test, y_test) = tf.keras.datasets.cifar10.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50000, 32, 32, 3)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Classes: 10\n"
     ]
    }
   ],
   "source": [
    "print('Total Classes:', len(np.unique(np.reshape(y_train, -1))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "features_dict = {\n",
    "    0: 'airplane',\n",
    "    1: 'car',\n",
    "    2: 'bird',\n",
    "    3: 'cat',\n",
    "    4: 'deer',\n",
    "    5: 'dog',\n",
    "    6: 'frog',\n",
    "    7: 'horse',\n",
    "    8: 'ship',\n",
    "    9: 'truck'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (5,5))\n",
    "for i in range(1,10):\n",
    "    plt.subplot(3,3,i)\n",
    "    sample_index = np.random.randint(0,x_train.shape[0])\n",
    "    sample_label = int(y_train[sample_index])\n",
    "    plt.imshow(x_train[sample_index,:,:,:])\n",
    "    plt.title(f'Label: {features_dict[sample_label]} ({sample_label})')\n",
    "    plt.axis(False)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_datagen = ImageDataGenerator(\n",
    "                        rescale = 1./255,\n",
    "                        rotation_range=40,\n",
    "                        width_shift_range=0.2,\n",
    "                        height_shift_range=0.2,\n",
    "                        shear_range=0.2,\n",
    "                        zoom_range=0.2,\n",
    "                        horizontal_flip=True,\n",
    "                        fill_mode='nearest')\n",
    "train_datagen.fit(x_train)\n",
    "\n",
    "x_test = x_test/255"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Lets test the dataset using ResNet\n",
    "- https://arxiv.org/pdf/1512.03385.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = ResNet50(n_classes = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_dir = os.path.join(r'.\\logs\\scalars',datetime.datetime.now().strftime(\"%Y%m%d-%H%M\")) \n",
    "\n",
    "file_writer = tf.summary.create_file_writer(os.path.join(log_dir, 'metrics'))\n",
    "file_writer.set_as_default()\n",
    "\n",
    "def lr_scheduler(epoch):\n",
    "    init_lr = 0.01\n",
    "    decay_steps = 160\n",
    "    decay_rate = 0.1\n",
    "    stepwise = True\n",
    "    \n",
    "    p = epoch / decay_steps\n",
    "    \n",
    "    if stepwise is True: \n",
    "        p = math_ops.floor(p)\n",
    "    \n",
    "    lr_exp_decay = math_ops.multiply(init_lr, math_ops.pow(decay_rate, p))\n",
    "    tf.summary.scalar('learning rate', data=lr_exp_decay, step=epoch)\n",
    "    return lr_exp_decay\n",
    "    \n",
    "lr_callback = tf.keras.callbacks.LearningRateScheduler(lr_scheduler)\n",
    "tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir)\n",
    "\n",
    "optimizer = tf.keras.optimizers.SGD(momentum=0.9,\n",
    "                                    decay = 0.0001)\n",
    "\n",
    "model.compile(loss ='sparse_categorical_crossentropy',\n",
    "              optimizer = optimizer,\n",
    "              metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Reusing TensorBoard on port 8089 (pid 16112), started 12:36:22 ago. (Use '!kill 16112' to kill it.)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "      <iframe id=\"tensorboard-frame-585ee73c23d8ec25\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
       "      </iframe>\n",
       "      <script>\n",
       "        (function() {\n",
       "          const frame = document.getElementById(\"tensorboard-frame-585ee73c23d8ec25\");\n",
       "          const url = new URL(\"/\", window.location);\n",
       "          url.port = 8089;\n",
       "          frame.src = url;\n",
       "        })();\n",
       "      </script>\n",
       "  "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%tensorboard --logdir logs/scalars --host localhost --port 8089"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train for 196 steps, validate on 10000 samples\n",
      "Epoch 1/150\n",
      "  1/196 [..............................] - ETA: 1:18:46 - loss: 3.0615 - accuracy: 0.0820WARNING:tensorflow:Method (on_train_batch_end) is slow compared to the batch update (0.213445). Check your callbacks.\n",
      "196/196 [==============================] - 65s 334ms/step - loss: 2.5302 - accuracy: 0.1731 - val_loss: 25.1191 - val_accuracy: 0.1148\n",
      "Epoch 2/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 2.2609 - accuracy: 0.2201 - val_loss: 2.4216 - val_accuracy: 0.1394\n",
      "Epoch 3/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 2.0664 - accuracy: 0.2854 - val_loss: 1.9715 - val_accuracy: 0.2530\n",
      "Epoch 4/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 1.9742 - accuracy: 0.3243 - val_loss: 1.8721 - val_accuracy: 0.3335\n",
      "Epoch 5/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.8758 - accuracy: 0.3506 - val_loss: 1.7169 - val_accuracy: 0.4047\n",
      "Epoch 6/150\n",
      "196/196 [==============================] - 38s 191ms/step - loss: 1.8265 - accuracy: 0.3647 - val_loss: 1.6973 - val_accuracy: 0.4056\n",
      "Epoch 7/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.7604 - accuracy: 0.3855 - val_loss: 1.5736 - val_accuracy: 0.4410\n",
      "Epoch 8/150\n",
      "196/196 [==============================] - 41s 209ms/step - loss: 1.7145 - accuracy: 0.3950 - val_loss: 1.5401 - val_accuracy: 0.4444\n",
      "Epoch 9/150\n",
      "196/196 [==============================] - 38s 196ms/step - loss: 1.6564 - accuracy: 0.4099 - val_loss: 1.5084 - val_accuracy: 0.4489\n",
      "Epoch 10/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 1.6238 - accuracy: 0.4202 - val_loss: 1.4800 - val_accuracy: 0.4701\n",
      "Epoch 11/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.5919 - accuracy: 0.4288 - val_loss: 1.4861 - val_accuracy: 0.4678\n",
      "Epoch 12/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.5749 - accuracy: 0.4384 - val_loss: 1.4181 - val_accuracy: 0.4987\n",
      "Epoch 13/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.5511 - accuracy: 0.4447 - val_loss: 1.5315 - val_accuracy: 0.4724\n",
      "Epoch 14/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 1.5350 - accuracy: 0.4497 - val_loss: 1.4038 - val_accuracy: 0.4940\n",
      "Epoch 15/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.5137 - accuracy: 0.4607 - val_loss: 1.4050 - val_accuracy: 0.5073\n",
      "Epoch 16/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 1.4965 - accuracy: 0.4650 - val_loss: 1.3965 - val_accuracy: 0.5045\n",
      "Epoch 17/150\n",
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      "Epoch 18/150\n",
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      "Epoch 19/150\n",
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      "Epoch 20/150\n",
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      "Epoch 23/150\n",
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      "Epoch 26/150\n",
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      "Epoch 28/150\n",
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      "Epoch 29/150\n",
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      "Epoch 30/150\n",
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      "Epoch 31/150\n",
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      "Epoch 32/150\n",
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      "Epoch 34/150\n",
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      "Epoch 35/150\n",
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      "Epoch 36/150\n",
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      "Epoch 37/150\n",
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      "Epoch 38/150\n",
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      "Epoch 39/150\n",
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      "Epoch 40/150\n",
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      "Epoch 41/150\n",
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      "Epoch 42/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.2360 - accuracy: 0.5601 - val_loss: 1.1577 - val_accuracy: 0.5885\n",
      "Epoch 43/150\n",
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      "Epoch 44/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.2236 - accuracy: 0.5628 - val_loss: 1.2091 - val_accuracy: 0.6003\n",
      "Epoch 45/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.2174 - accuracy: 0.5646 - val_loss: 1.1516 - val_accuracy: 0.5911\n",
      "Epoch 46/150\n",
      "196/196 [==============================] - 38s 191ms/step - loss: 1.2129 - accuracy: 0.5652 - val_loss: 1.1578 - val_accuracy: 0.5982\n",
      "Epoch 47/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.2095 - accuracy: 0.5692 - val_loss: 1.1428 - val_accuracy: 0.5904\n",
      "Epoch 48/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 1.2028 - accuracy: 0.5714 - val_loss: 1.0950 - val_accuracy: 0.6211\n",
      "Epoch 49/150\n",
      "196/196 [==============================] - 38s 191ms/step - loss: 1.1997 - accuracy: 0.5707 - val_loss: 1.1075 - val_accuracy: 0.6134\n",
      "Epoch 50/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.1899 - accuracy: 0.5753 - val_loss: 1.0826 - val_accuracy: 0.6208\n",
      "Epoch 51/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.1826 - accuracy: 0.5769 - val_loss: 1.1275 - val_accuracy: 0.6086\n",
      "Epoch 52/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.1688 - accuracy: 0.5830 - val_loss: 1.1241 - val_accuracy: 0.6095\n",
      "Epoch 53/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 1.1713 - accuracy: 0.5817 - val_loss: 1.0881 - val_accuracy: 0.6197\n",
      "Epoch 54/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.1659 - accuracy: 0.5837 - val_loss: 1.0863 - val_accuracy: 0.6135\n",
      "Epoch 55/150\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "196/196 [==============================] - 38s 194ms/step - loss: 1.1606 - accuracy: 0.5869 - val_loss: 1.1018 - val_accuracy: 0.6197\n",
      "Epoch 56/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 1.1572 - accuracy: 0.5845 - val_loss: 1.1449 - val_accuracy: 0.6022\n",
      "Epoch 57/150\n",
      "196/196 [==============================] - 37s 189ms/step - loss: 1.1514 - accuracy: 0.5888 - val_loss: 1.0988 - val_accuracy: 0.6082\n",
      "Epoch 58/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 1.1466 - accuracy: 0.5899 - val_loss: 1.1881 - val_accuracy: 0.5894\n",
      "Epoch 59/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.1393 - accuracy: 0.5928 - val_loss: 1.0970 - val_accuracy: 0.6220\n",
      "Epoch 60/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 1.1359 - accuracy: 0.5952 - val_loss: 1.0751 - val_accuracy: 0.6173\n",
      "Epoch 61/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 1.1274 - accuracy: 0.5971 - val_loss: 1.0559 - val_accuracy: 0.6289\n",
      "Epoch 62/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.1232 - accuracy: 0.6008 - val_loss: 1.1124 - val_accuracy: 0.6126\n",
      "Epoch 63/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.1149 - accuracy: 0.6013 - val_loss: 1.0855 - val_accuracy: 0.6178\n",
      "Epoch 64/150\n",
      "196/196 [==============================] - 37s 189ms/step - loss: 1.1164 - accuracy: 0.6011 - val_loss: 1.0345 - val_accuracy: 0.6359\n",
      "Epoch 65/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.1136 - accuracy: 0.6013 - val_loss: 1.1524 - val_accuracy: 0.6158\n",
      "Epoch 66/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.1046 - accuracy: 0.6058 - val_loss: 1.0441 - val_accuracy: 0.6283\n",
      "Epoch 67/150\n",
      "196/196 [==============================] - 37s 186ms/step - loss: 1.1015 - accuracy: 0.6087 - val_loss: 1.0852 - val_accuracy: 0.6298\n",
      "Epoch 68/150\n",
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      "Epoch 69/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0929 - accuracy: 0.6103 - val_loss: 1.0664 - val_accuracy: 0.6268\n",
      "Epoch 70/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 1.0895 - accuracy: 0.6113 - val_loss: 1.0560 - val_accuracy: 0.6317\n",
      "Epoch 71/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 1.0821 - accuracy: 0.6157 - val_loss: 1.1072 - val_accuracy: 0.6335\n",
      "Epoch 72/150\n",
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      "Epoch 73/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 1.0750 - accuracy: 0.6170 - val_loss: 1.0826 - val_accuracy: 0.6321\n",
      "Epoch 74/150\n",
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      "Epoch 75/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0683 - accuracy: 0.6193 - val_loss: 1.0939 - val_accuracy: 0.6256\n",
      "Epoch 76/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0624 - accuracy: 0.6219 - val_loss: 1.0269 - val_accuracy: 0.6400\n",
      "Epoch 77/150\n",
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      "Epoch 78/150\n",
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      "Epoch 79/150\n",
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      "Epoch 80/150\n",
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      "Epoch 81/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0432 - accuracy: 0.6279 - val_loss: 1.0546 - val_accuracy: 0.6367\n",
      "Epoch 82/150\n",
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      "Epoch 83/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0344 - accuracy: 0.6300 - val_loss: 1.0317 - val_accuracy: 0.6442\n",
      "Epoch 84/150\n",
      "196/196 [==============================] - 36s 186ms/step - loss: 1.0296 - accuracy: 0.6329 - val_loss: 1.1984 - val_accuracy: 0.6390\n",
      "Epoch 85/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0252 - accuracy: 0.6346 - val_loss: 1.1699 - val_accuracy: 0.6376\n",
      "Epoch 86/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0232 - accuracy: 0.6350 - val_loss: 1.0057 - val_accuracy: 0.6489\n",
      "Epoch 87/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0219 - accuracy: 0.6369 - val_loss: 1.0512 - val_accuracy: 0.6297\n",
      "Epoch 88/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 1.0191 - accuracy: 0.6365 - val_loss: 1.0737 - val_accuracy: 0.6219\n",
      "Epoch 89/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 1.0124 - accuracy: 0.6382 - val_loss: 1.0819 - val_accuracy: 0.6360\n",
      "Epoch 90/150\n",
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      "Epoch 92/150\n",
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      "Epoch 93/150\n",
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      "Epoch 94/150\n",
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      "Epoch 95/150\n",
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      "Epoch 96/150\n",
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      "Epoch 97/150\n",
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      "Epoch 98/150\n",
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      "Epoch 99/150\n",
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      "Epoch 100/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 0.9734 - accuracy: 0.6493 - val_loss: 1.0148 - val_accuracy: 0.6476\n",
      "Epoch 101/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.9703 - accuracy: 0.6516 - val_loss: 1.0991 - val_accuracy: 0.6446\n",
      "Epoch 102/150\n",
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      "Epoch 103/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.9642 - accuracy: 0.6529 - val_loss: 1.4418 - val_accuracy: 0.6228\n",
      "Epoch 104/150\n",
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      "Epoch 105/150\n",
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      "Epoch 106/150\n",
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      "Epoch 107/150\n",
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      "Epoch 109/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 0.9432 - accuracy: 0.6624 - val_loss: 1.2212 - val_accuracy: 0.6289\n",
      "Epoch 110/150\n"
     ]
    },
    {
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     "text": [
      "196/196 [==============================] - 38s 195ms/step - loss: 0.9471 - accuracy: 0.6597 - val_loss: 1.2286 - val_accuracy: 0.6455\n",
      "Epoch 111/150\n",
      "196/196 [==============================] - 38s 194ms/step - loss: 0.9341 - accuracy: 0.6669 - val_loss: 1.5422 - val_accuracy: 0.6416\n",
      "Epoch 112/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.9314 - accuracy: 0.6667 - val_loss: 2.0342 - val_accuracy: 0.6529\n",
      "Epoch 113/150\n",
      "196/196 [==============================] - 39s 199ms/step - loss: 0.9295 - accuracy: 0.6679 - val_loss: 1.1525 - val_accuracy: 0.6458\n",
      "Epoch 114/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.9293 - accuracy: 0.6665 - val_loss: 1.2690 - val_accuracy: 0.6455\n",
      "Epoch 115/150\n",
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      "Epoch 116/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 0.9200 - accuracy: 0.6715 - val_loss: 1.4186 - val_accuracy: 0.6600\n",
      "Epoch 117/150\n",
      "196/196 [==============================] - 37s 187ms/step - loss: 0.9151 - accuracy: 0.6734 - val_loss: 1.4478 - val_accuracy: 0.6512\n",
      "Epoch 118/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 0.9115 - accuracy: 0.6723 - val_loss: 1.2200 - val_accuracy: 0.6488\n",
      "Epoch 119/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 0.9071 - accuracy: 0.6728 - val_loss: 1.5069 - val_accuracy: 0.6521\n",
      "Epoch 120/150\n",
      "196/196 [==============================] - 37s 191ms/step - loss: 0.9145 - accuracy: 0.6725 - val_loss: 1.1945 - val_accuracy: 0.6426\n",
      "Epoch 121/150\n",
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      "Epoch 122/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 0.8997 - accuracy: 0.6794 - val_loss: 1.4563 - val_accuracy: 0.6642\n",
      "Epoch 123/150\n",
      "196/196 [==============================] - 37s 188ms/step - loss: 0.8984 - accuracy: 0.6775 - val_loss: 1.6392 - val_accuracy: 0.6475\n",
      "Epoch 124/150\n",
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      "Epoch 125/150\n",
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      "Epoch 126/150\n",
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      "Epoch 127/150\n",
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      "Epoch 128/150\n",
      "196/196 [==============================] - 38s 196ms/step - loss: 0.8849 - accuracy: 0.6839 - val_loss: 1.3017 - val_accuracy: 0.6590\n",
      "Epoch 129/150\n",
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      "Epoch 130/150\n",
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      "Epoch 131/150\n",
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      "Epoch 132/150\n",
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      "Epoch 133/150\n",
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      "Epoch 134/150\n",
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      "Epoch 135/150\n",
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      "Epoch 136/150\n",
      "196/196 [==============================] - 40s 203ms/step - loss: 0.8551 - accuracy: 0.6916 - val_loss: 1.1005 - val_accuracy: 0.6494\n",
      "Epoch 137/150\n",
      "196/196 [==============================] - 39s 198ms/step - loss: 0.8554 - accuracy: 0.6917 - val_loss: 1.3660 - val_accuracy: 0.6560\n",
      "Epoch 138/150\n",
      "196/196 [==============================] - 39s 200ms/step - loss: 0.8501 - accuracy: 0.6957 - val_loss: 1.3585 - val_accuracy: 0.6440\n",
      "Epoch 139/150\n",
      "196/196 [==============================] - 38s 193ms/step - loss: 0.8527 - accuracy: 0.6934 - val_loss: 1.0523 - val_accuracy: 0.6544\n",
      "Epoch 140/150\n",
      "196/196 [==============================] - 39s 199ms/step - loss: 0.8485 - accuracy: 0.6966 - val_loss: 1.4762 - val_accuracy: 0.6598\n",
      "Epoch 141/150\n",
      "196/196 [==============================] - 39s 198ms/step - loss: 0.8402 - accuracy: 0.6984 - val_loss: 1.6630 - val_accuracy: 0.6530\n",
      "Epoch 142/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.8396 - accuracy: 0.6989 - val_loss: 1.1181 - val_accuracy: 0.6596\n",
      "Epoch 143/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.8360 - accuracy: 0.7008 - val_loss: 0.9957 - val_accuracy: 0.6669\n",
      "Epoch 144/150\n",
      "196/196 [==============================] - 38s 195ms/step - loss: 0.8347 - accuracy: 0.6996 - val_loss: 1.5456 - val_accuracy: 0.6596\n",
      "Epoch 145/150\n",
      "196/196 [==============================] - 39s 199ms/step - loss: 0.8384 - accuracy: 0.6997 - val_loss: 1.2201 - val_accuracy: 0.6493\n",
      "Epoch 146/150\n",
      "196/196 [==============================] - 39s 197ms/step - loss: 0.8288 - accuracy: 0.7035 - val_loss: 1.2152 - val_accuracy: 0.6453\n",
      "Epoch 147/150\n",
      "196/196 [==============================] - 38s 192ms/step - loss: 0.8207 - accuracy: 0.7063 - val_loss: 1.0454 - val_accuracy: 0.6547\n",
      "Epoch 148/150\n",
      "196/196 [==============================] - 37s 189ms/step - loss: 0.8198 - accuracy: 0.7066 - val_loss: 1.2260 - val_accuracy: 0.6545\n",
      "Epoch 149/150\n",
      "196/196 [==============================] - 39s 199ms/step - loss: 0.8150 - accuracy: 0.7081 - val_loss: 1.2268 - val_accuracy: 0.6635\n",
      "Epoch 150/150\n",
      "196/196 [==============================] - 39s 199ms/step - loss: 0.8138 - accuracy: 0.7085 - val_loss: 1.4409 - val_accuracy: 0.6504\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(train_datagen.flow(x_train, y_train, batch_size = 256),\n",
    "                    epochs = 150,\n",
    "                    validation_data = (x_test, y_test),\n",
    "                    callbacks = [tensorboard_callback, lr_callback],\n",
    "                    verbose = 1)\n",
    "#lr_callback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy', 'lr'])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,10))\n",
    "plt.plot(history.history['accuracy'])\n",
    "plt.plot(history.history['val_accuracy'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}