{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n" ] } ], "source": [ "from keras import optimizers, regularizers\n", "from keras.layers import Dense, Dropout, Input\n", "from keras.models import Model, Sequential\n", "from random import shuffle\n", "from scipy import interp\n", "from sklearn.linear_model import LogisticRegression\n", "from scipy.stats.mstats import gmean\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.metrics import roc_curve, auc\n", "from sklearn.model_selection import StratifiedKFold, train_test_split\n", "from sklearn.preprocessing import QuantileTransformer\n", "import contextlib\n", "import glob\n", "import gzip\n", "import h5py\n", "import keras\n", "import numpy as np\n", "import os\n", "import pandas as pd\n", "import pylab as plt\n", "import random\n", "import scipy\n", "import sklearn\n", "import tensorflow as tf\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.datasets import make_classification\n", "from sklearn.svm import SVC\n", "\n", "\n", "random_state = np.random.RandomState(0)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"X_f = '/home/drewe/notebooks/genotox/GenoTox-database.csv'\\ny_f = '/home/drewe/notebooks/genotox/outcome-mod-2.csv'\\n\\nX = pd.read_csv(X_f).values[:,:-1]\\ny = pd.read_csv(y_f).values\\n\\n\\nix = [i for i in range(y.shape[0])]\\nshuffle(ix)\\nX = X[ix, :]\\ny = y[ix]\\nnames = pd.read_csv(X_f)['Unnamed: 0'][ix].values\\nX = sklearn.preprocessing.quantile_transform(X, axis=1, output_distribution='uniform', copy=True)\\ny = y[: ,0]\\n\"" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "'''X_f = '/home/drewe/notebooks/genotox/GenoTox-database.csv'\n", "y_f = '/home/drewe/notebooks/genotox/outcome-mod-2.csv'\n", "\n", "X = pd.read_csv(X_f).values[:,:-1]\n", "y = pd.read_csv(y_f).values\n", "\n", "\n", "ix = [i for i in range(y.shape[0])]\n", "shuffle(ix)\n", "X = X[ix, :]\n", "y = y[ix]\n", "names = pd.read_csv(X_f)['Unnamed: 0'][ix].values\n", "X = sklearn.preprocessing.quantile_transform(X, axis=1, output_distribution='uniform', copy=True)\n", "y = y[: ,0]\n", "'''\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "X_f_ext = '/home/drewe/notebooks/genotox/mutagenicity-fingerprints.csv'\n", "\n", "X = pd.read_csv(X_f_ext,sep=',')\n", "X['Mutagenicity_bin'] = np.int32(X['Mutagenicity'] == 'mutagenic')\n", "del X['Mutagenicity']\n", "\n", "X_f_ext = '/home/drewe/notebooks/genotox/mutagenicity-mod-2.csv'\n", "\n", "X_ext = pd.read_csv(X_f_ext,sep=';')\n", "\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "X = pd.merge(X[['Canonical SMILES','Mutagenicity_bin']], X_ext, left_on='Canonical SMILES', right_on='Name')\n", "y = X['Mutagenicity_bin'].values\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [], "source": [ "#X.to_csv('/home/drewe/notebooks/genotox/mutagenicity-mod-2.new.csv')\n", "#X.set_index('Canonical SMILES').to_csv('/home/drewe/notebooks/genotox/mutagenicity-mod-2.new.csv')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "del X['Mutagenicity_bin']\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "names = X['Name'].values\n", "del X['Name']\n", "\n", "X = np.float64(X.values[:,1:])\n", "\n", "ix = [i for i in range(y.shape[0])]\n", "shuffle(ix)\n", "X = X[ix, :]\n", "names = names[ix]\n", "y = y[ix]\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(8083, 1442)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.shape" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1693 - acc: 0.9270\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1661 - acc: 0.9289\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.1582 - acc: 0.9326\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1633 - acc: 0.9282\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1675 - acc: 0.9314\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1350 - acc: 0.9442\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1327 - acc: 0.9427\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1340 - acc: 0.9472\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1330 - acc: 0.9456\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.1180 - acc: 0.9520\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 56us/step - loss: 0.1220 - acc: 0.9501\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1212 - acc: 0.9482\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1194 - acc: 0.9506\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1184 - acc: 0.9506\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1213 - acc: 0.9526\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1288 - acc: 0.9464\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.1379 - acc: 0.9439\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1168 - acc: 0.9530\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.0971 - acc: 0.9625\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 49us/step - loss: 0.1040 - acc: 0.9594\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0970 - acc: 0.9589\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.0902 - acc: 0.9655\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1191 - acc: 0.9509\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.0916 - acc: 0.9629\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.1164 - acc: 0.9520\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0983 - acc: 0.9593\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0968 - acc: 0.9612\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.1180 - acc: 0.9523\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1149 - acc: 0.9557\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0887 - acc: 0.9643\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0837 - acc: 0.9682\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0812 - acc: 0.9685\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0789 - acc: 0.9688\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0654 - acc: 0.9735\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.0744 - acc: 0.9713\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 49us/step - loss: 0.0843 - acc: 0.9693\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1127 - acc: 0.9567\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1128 - acc: 0.9539\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0773 - acc: 0.9700\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.0923 - acc: 0.9634\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0778 - acc: 0.9662\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0878 - acc: 0.9636\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0791 - acc: 0.9691\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0579 - acc: 0.9764\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0534 - acc: 0.9795\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0735 - acc: 0.9704\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0852 - acc: 0.9662\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0734 - acc: 0.9707\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0755 - acc: 0.9702\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1073 - acc: 0.9586\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1529 - acc: 0.9402\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1557 - acc: 0.9357\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1735 - acc: 0.9258\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1615 - acc: 0.9324\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1458 - acc: 0.9412\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1536 - acc: 0.9376\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1413 - acc: 0.9438\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1492 - acc: 0.9374\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1385 - acc: 0.9440\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1533 - acc: 0.9403\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1382 - acc: 0.9465\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1243 - acc: 0.9513\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1354 - acc: 0.9454\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1306 - acc: 0.9476\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1171 - acc: 0.9559\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1123 - acc: 0.9564\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1252 - acc: 0.9526\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1059 - acc: 0.9559\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1142 - acc: 0.9534\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1278 - acc: 0.9490\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1281 - acc: 0.9475\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1136 - acc: 0.9555\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1120 - acc: 0.9553\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0974 - acc: 0.9621\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1008 - acc: 0.9597\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1062 - acc: 0.9567\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1198 - acc: 0.9524\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0970 - acc: 0.9632\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0908 - acc: 0.9652\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1201 - acc: 0.9523\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0916 - acc: 0.9645\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.0868 - acc: 0.9663\n", "Epoch 33/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 40us/step - loss: 0.0765 - acc: 0.9699\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0824 - acc: 0.9678\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0888 - acc: 0.9629\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0841 - acc: 0.9674\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0816 - acc: 0.9685\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0783 - acc: 0.9688\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0996 - acc: 0.9652\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1062 - acc: 0.9581\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0755 - acc: 0.9711\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0700 - acc: 0.9737\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0630 - acc: 0.9753\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0773 - acc: 0.9688\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0808 - acc: 0.9689\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0619 - acc: 0.9754\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0648 - acc: 0.9742\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0695 - acc: 0.9732\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0797 - acc: 0.9704\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0690 - acc: 0.9722\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1820 - acc: 0.9271\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1747 - acc: 0.9322\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1474 - acc: 0.9406\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1626 - acc: 0.9330\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1585 - acc: 0.9332\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1480 - acc: 0.9405\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1529 - acc: 0.9387\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1478 - acc: 0.9416\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1401 - acc: 0.9447\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1558 - acc: 0.9358\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1404 - acc: 0.9421\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1276 - acc: 0.9491\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1162 - acc: 0.9546\n", "Epoch 14/50\n", "7274/7274 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[==============================] - 0s 39us/step - loss: 0.0929 - acc: 0.9638\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1139 - acc: 0.9542\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0745 - acc: 0.9720\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0997 - acc: 0.9597\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0899 - acc: 0.9632\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0754 - acc: 0.9695\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0767 - acc: 0.9709\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0705 - acc: 0.9733\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0781 - acc: 0.9706\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0998 - acc: 0.9615\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0814 - acc: 0.9703\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0673 - acc: 0.9739\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0735 - acc: 0.9704\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0766 - acc: 0.9678\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0807 - acc: 0.9674\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0998 - acc: 0.9623\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0621 - acc: 0.9759\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0541 - acc: 0.9805\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0609 - acc: 0.9755\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1501 - acc: 0.9376\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1426 - acc: 0.9440\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1339 - acc: 0.9461\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1443 - acc: 0.9445\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1226 - acc: 0.9516\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1395 - acc: 0.9428\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1379 - acc: 0.9429\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1402 - acc: 0.9424\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1191 - acc: 0.9516\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1050 - acc: 0.9563\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1218 - acc: 0.9517\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1026 - acc: 0.9572\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1051 - acc: 0.9572\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1177 - acc: 0.9520\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1169 - acc: 0.9520\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 16/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1141 - acc: 0.9535\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1002 - acc: 0.9582\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0902 - acc: 0.9640\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0897 - acc: 0.9656\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1018 - acc: 0.9588\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1135 - acc: 0.9577\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1095 - acc: 0.9553\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0724 - acc: 0.9732\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0939 - acc: 0.9636\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0959 - acc: 0.9623\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1040 - acc: 0.9585\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1036 - acc: 0.9597\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1061 - acc: 0.9566\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0722 - acc: 0.9710\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0748 - acc: 0.9695\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0956 - acc: 0.9592\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0933 - acc: 0.9636\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0779 - acc: 0.9687\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0668 - acc: 0.9742\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0646 - acc: 0.9736\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0676 - acc: 0.9722\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0682 - acc: 0.9746\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0891 - acc: 0.9645\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0601 - acc: 0.9758\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0711 - acc: 0.9728\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0555 - acc: 0.9794\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0761 - acc: 0.9691\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0806 - acc: 0.9695\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0623 - acc: 0.9742\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0598 - acc: 0.9777\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0534 - acc: 0.9801\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0654 - acc: 0.9746\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0491 - acc: 0.9820\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0611 - acc: 0.9769\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0633 - acc: 0.9746\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1391 - acc: 0.9431\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1574 - acc: 0.9362\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1334 - acc: 0.9449\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1339 - acc: 0.9446\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 58us/step - loss: 0.1360 - acc: 0.9431\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.1426 - acc: 0.9439\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1232 - acc: 0.9515\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1243 - acc: 0.9476\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1148 - acc: 0.9553\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1407 - acc: 0.9401\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1106 - acc: 0.9557\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1204 - acc: 0.9524\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.1115 - acc: 0.9531\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1218 - acc: 0.9528\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1030 - acc: 0.9570\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1170 - acc: 0.9535\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0941 - acc: 0.9616\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0868 - acc: 0.9644\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0921 - acc: 0.9652\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1297 - acc: 0.9490\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0983 - acc: 0.9593\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0812 - acc: 0.9696\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0826 - acc: 0.9654\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0775 - acc: 0.9703\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1082 - acc: 0.9577\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1050 - acc: 0.9589\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0745 - acc: 0.9704\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0872 - acc: 0.9663\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1020 - acc: 0.9588\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0745 - acc: 0.9706\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0657 - acc: 0.9739\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0583 - acc: 0.9770\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0586 - acc: 0.9754\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0870 - acc: 0.9656\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0789 - acc: 0.9702\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0834 - acc: 0.9692\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0724 - acc: 0.9742\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0804 - acc: 0.9687\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0771 - acc: 0.9699\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0716 - acc: 0.9707\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0656 - acc: 0.9758\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0675 - acc: 0.9720\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0797 - acc: 0.9665\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0679 - acc: 0.9726\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0738 - acc: 0.9732\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0642 - acc: 0.9755\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0564 - acc: 0.9783\n", "Epoch 48/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 41us/step - loss: 0.0496 - acc: 0.9823\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0657 - acc: 0.9732\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0513 - acc: 0.9795\n", " 0.9200790866530578\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1470 - acc: 0.9381\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1375 - acc: 0.9440\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1425 - acc: 0.9391\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1526 - acc: 0.9401\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1239 - acc: 0.9468\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1120 - acc: 0.9552\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1291 - acc: 0.9447\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1226 - acc: 0.9500\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1254 - acc: 0.9501\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1137 - acc: 0.9530\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1307 - acc: 0.9456\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0985 - acc: 0.9596\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1301 - acc: 0.9469\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1027 - acc: 0.9589\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1050 - acc: 0.9564\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1227 - acc: 0.9478\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1094 - acc: 0.9537\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.1091 - acc: 0.9563\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0866 - acc: 0.9655\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0818 - acc: 0.9670\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0955 - acc: 0.9597\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0770 - acc: 0.9706\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0927 - acc: 0.9637\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1084 - acc: 0.9583\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0894 - acc: 0.9663\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0691 - acc: 0.9722\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0993 - acc: 0.9581\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1062 - acc: 0.9557\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0685 - acc: 0.9732\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0750 - acc: 0.9718\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0849 - acc: 0.9645\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0897 - acc: 0.9632\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0771 - acc: 0.9684\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0676 - acc: 0.9742\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0751 - acc: 0.9702\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0663 - acc: 0.9739\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0898 - acc: 0.9616\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1025 - acc: 0.9575\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0948 - acc: 0.9614\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0662 - acc: 0.9717\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0539 - acc: 0.9802\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0475 - acc: 0.9808\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0520 - acc: 0.9802\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0532 - acc: 0.9792\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0520 - acc: 0.9783\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0692 - acc: 0.9706\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0510 - acc: 0.9802\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.0563 - acc: 0.9784\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0480 - acc: 0.9805\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0611 - acc: 0.9764\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1616 - acc: 0.9310\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1548 - acc: 0.9355\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1743 - acc: 0.9274\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1477 - acc: 0.9425\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1662 - acc: 0.9307\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1452 - acc: 0.9406\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1291 - acc: 0.9482\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1383 - acc: 0.9454\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1303 - acc: 0.9471\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1290 - acc: 0.9451\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1188 - acc: 0.9498\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1238 - acc: 0.9493\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1309 - acc: 0.9451\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1270 - acc: 0.9468\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1112 - acc: 0.9563\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1068 - acc: 0.9570\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1234 - acc: 0.9494\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1162 - acc: 0.9535\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1201 - acc: 0.9528\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1021 - acc: 0.9610\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0873 - acc: 0.9658\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0939 - acc: 0.9626\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1024 - acc: 0.9585\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1037 - acc: 0.9566\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1140 - acc: 0.9548\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1157 - acc: 0.9527\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0839 - acc: 0.9656\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0973 - acc: 0.9608\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0798 - acc: 0.9685\n", "Epoch 30/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 41us/step - loss: 0.0991 - acc: 0.9597\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0803 - acc: 0.9695\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1036 - acc: 0.9596\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0827 - acc: 0.9669\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0760 - acc: 0.9713\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0742 - acc: 0.9707\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0651 - acc: 0.9746\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0770 - acc: 0.9710\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0764 - acc: 0.9713\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0675 - acc: 0.9737\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0716 - acc: 0.9706\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0557 - acc: 0.9797\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0711 - acc: 0.9735\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0763 - acc: 0.9713\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0790 - acc: 0.9689\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0762 - acc: 0.9710\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0593 - acc: 0.9772\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0615 - acc: 0.9755\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0628 - acc: 0.9753\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0613 - acc: 0.9751\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0703 - acc: 0.9725\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1724 - acc: 0.9274\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1393 - acc: 0.9440\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1522 - acc: 0.9363\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1544 - acc: 0.9357\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1358 - acc: 0.9418\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1178 - acc: 0.9511\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1354 - acc: 0.9450\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1263 - acc: 0.9476\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1388 - acc: 0.9431\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1212 - acc: 0.9493\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1306 - acc: 0.9469\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1076 - acc: 0.9592\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1102 - acc: 0.9553\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1257 - acc: 0.9467\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1129 - acc: 0.9516\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1172 - acc: 0.9524\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1167 - acc: 0.9506\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1000 - acc: 0.9572\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1005 - acc: 0.9593\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1017 - acc: 0.9567\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0971 - acc: 0.9594\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1217 - acc: 0.9484\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0912 - acc: 0.9633\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0846 - acc: 0.9636\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1129 - acc: 0.9538\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0787 - acc: 0.9680\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0995 - acc: 0.9597\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0868 - acc: 0.9651\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0843 - acc: 0.9665\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1067 - acc: 0.9581\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0863 - acc: 0.9651\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1027 - acc: 0.9593\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0740 - acc: 0.9709\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0662 - acc: 0.9725\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0825 - acc: 0.9662\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0844 - acc: 0.9658\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0672 - acc: 0.9711\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0606 - acc: 0.9755\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0561 - acc: 0.9792\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0805 - acc: 0.9670\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0993 - acc: 0.9597\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0635 - acc: 0.9755\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0521 - acc: 0.9801\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0580 - acc: 0.9750\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0693 - acc: 0.9720\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0616 - acc: 0.9757\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0607 - acc: 0.9758\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0782 - acc: 0.9693\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0496 - acc: 0.9801\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0693 - acc: 0.9737\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1294 - acc: 0.9468\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1401 - acc: 0.9449\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1313 - acc: 0.9428\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1262 - acc: 0.9495\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1343 - acc: 0.9484\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1222 - acc: 0.9498\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1156 - acc: 0.9515\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1229 - acc: 0.9509\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1210 - acc: 0.9491\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1021 - acc: 0.9590\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1071 - acc: 0.9564\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1524 - acc: 0.9383\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 13/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1058 - acc: 0.9557\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0976 - acc: 0.9596\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1009 - acc: 0.9574\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0971 - acc: 0.9594\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0834 - acc: 0.9647\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0850 - acc: 0.9644\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.0958 - acc: 0.9622\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0929 - acc: 0.9615\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0931 - acc: 0.9638\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0744 - acc: 0.9706\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1061 - acc: 0.9570\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0894 - acc: 0.9655\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0689 - acc: 0.9736\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0603 - acc: 0.9736\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0871 - acc: 0.9647\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0666 - acc: 0.9732\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0673 - acc: 0.9729\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0872 - acc: 0.9669\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0699 - acc: 0.9691\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1040 - acc: 0.9611\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0744 - acc: 0.9689\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0650 - acc: 0.9750\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0610 - acc: 0.9742\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0559 - acc: 0.9802\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0424 - acc: 0.9849\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0644 - acc: 0.9732\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0532 - acc: 0.9791\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0719 - acc: 0.9713\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0617 - acc: 0.9766\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0606 - acc: 0.9768\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0673 - acc: 0.9740\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0644 - acc: 0.9753\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0750 - acc: 0.9711\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0641 - acc: 0.9733\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0433 - acc: 0.9838\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0444 - acc: 0.9839\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0700 - acc: 0.9709\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0755 - acc: 0.9691\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1677 - acc: 0.9304\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1655 - acc: 0.9311\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1738 - acc: 0.9249\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1475 - acc: 0.9381\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1422 - acc: 0.9396\n", "Epoch 6/50\n", "7274/7274 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[==============================] - 0s 40us/step - loss: 0.1262 - acc: 0.9486\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1402 - acc: 0.9425\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1202 - acc: 0.9494\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1238 - acc: 0.9489\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1127 - acc: 0.9563\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1146 - acc: 0.9515\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1210 - acc: 0.9519\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0972 - acc: 0.9601\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1014 - acc: 0.9589\n", "Epoch 24/50\n", "7274/7274 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[==============================] - 0s 41us/step - loss: 0.0838 - acc: 0.9658\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0890 - acc: 0.9633\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0806 - acc: 0.9687\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0876 - acc: 0.9633\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0751 - acc: 0.9682\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0680 - acc: 0.9737\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1074 - acc: 0.9581\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0921 - acc: 0.9634\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0770 - acc: 0.9677\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0940 - acc: 0.9634\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.0668 - acc: 0.9739\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0618 - acc: 0.9737\n", "Epoch 45/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 41us/step - loss: 0.0754 - acc: 0.9693\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0581 - acc: 0.9750\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0745 - acc: 0.9688\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0655 - acc: 0.9735\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0774 - acc: 0.9691\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0861 - acc: 0.9651\n", " 0.9142881590045105\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1723 - acc: 0.9281\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1631 - acc: 0.9322\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1381 - acc: 0.9468\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1349 - acc: 0.9442\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1306 - acc: 0.9505\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.1315 - acc: 0.9460\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.1277 - acc: 0.9478\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1488 - acc: 0.9396\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.1206 - acc: 0.9517\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1092 - acc: 0.9575\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1225 - acc: 0.9506\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1371 - acc: 0.9457\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1095 - acc: 0.9546\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1180 - acc: 0.9535\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1063 - acc: 0.9570\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1220 - acc: 0.9489\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1236 - acc: 0.9502\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1148 - acc: 0.9542\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0823 - acc: 0.9669\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1131 - acc: 0.9550\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0922 - acc: 0.9615\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0808 - acc: 0.9682\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1061 - acc: 0.9572\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.0961 - acc: 0.9640\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0939 - acc: 0.9629\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1070 - acc: 0.9570\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0996 - acc: 0.9603\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0977 - acc: 0.9611\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1204 - acc: 0.9494\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0807 - acc: 0.9692\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0682 - acc: 0.9732\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0619 - acc: 0.9750\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0598 - acc: 0.9753\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0728 - acc: 0.9720\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0804 - acc: 0.9676\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0870 - acc: 0.9640\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0614 - acc: 0.9744\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0615 - acc: 0.9759\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.0794 - acc: 0.9696\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0638 - acc: 0.9740\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0601 - acc: 0.9750\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0514 - acc: 0.9805\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0601 - acc: 0.9757\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0940 - acc: 0.9648\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0512 - acc: 0.9799\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0428 - acc: 0.9847\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0477 - acc: 0.9809\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0598 - acc: 0.9761\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0550 - acc: 0.9795\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0642 - acc: 0.9748\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1445 - acc: 0.9413\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1447 - acc: 0.9396\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1341 - acc: 0.9450\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.1369 - acc: 0.9418\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1328 - acc: 0.9456\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1233 - acc: 0.9495\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1238 - acc: 0.9494\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1035 - acc: 0.9592\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1196 - acc: 0.9491\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1078 - acc: 0.9575\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1273 - acc: 0.9473\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1230 - acc: 0.9497\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.1083 - acc: 0.9575\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1086 - acc: 0.9560\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0792 - acc: 0.9678\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0909 - acc: 0.9622\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.1072 - acc: 0.9575\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0947 - acc: 0.9632\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.0910 - acc: 0.9634\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0935 - acc: 0.9619\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 45us/step - loss: 0.0811 - acc: 0.9667\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0873 - acc: 0.9649\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.0932 - acc: 0.9610\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0918 - acc: 0.9632\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0899 - acc: 0.9654\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0727 - acc: 0.9722\n", "Epoch 27/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 42us/step - loss: 0.0741 - acc: 0.9693\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1171 - acc: 0.9545\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1005 - acc: 0.9605\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0640 - acc: 0.9759\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0785 - acc: 0.9698\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0643 - acc: 0.9766\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0590 - acc: 0.9773\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0621 - acc: 0.9742\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1386 - acc: 0.9475\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0618 - acc: 0.9753\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0627 - acc: 0.9743\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0657 - acc: 0.9733\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0895 - acc: 0.9656\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0692 - acc: 0.9736\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0512 - acc: 0.9812\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0515 - acc: 0.9808\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0579 - acc: 0.9773\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0511 - acc: 0.9802\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0611 - acc: 0.9757\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.0636 - acc: 0.9758\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0378 - acc: 0.9858\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0371 - acc: 0.9863\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0524 - acc: 0.9783\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0533 - acc: 0.9784\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1543 - acc: 0.9365\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1474 - acc: 0.9398\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1522 - acc: 0.9380\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1359 - acc: 0.9456\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1382 - acc: 0.9413\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1491 - acc: 0.9402\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1280 - acc: 0.9473\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1170 - acc: 0.9524\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1238 - acc: 0.9502\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1179 - acc: 0.9531\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1273 - acc: 0.9479\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1022 - acc: 0.9588\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1203 - acc: 0.9526\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1021 - acc: 0.9574\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1135 - acc: 0.9535\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0978 - acc: 0.9590\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1067 - acc: 0.9577\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0819 - acc: 0.9682\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0874 - acc: 0.9648\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1049 - acc: 0.9567\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1017 - acc: 0.9592\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0869 - acc: 0.9654\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0783 - acc: 0.9682\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0679 - acc: 0.9742\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0899 - acc: 0.9647\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0678 - acc: 0.9748\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0825 - acc: 0.9684\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0765 - acc: 0.9696\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0890 - acc: 0.9654\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0801 - acc: 0.9707\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0944 - acc: 0.9652\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1225 - acc: 0.9542\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0618 - acc: 0.9775\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0513 - acc: 0.9802\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0787 - acc: 0.9695\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0630 - acc: 0.9755\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0679 - acc: 0.9732\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0537 - acc: 0.9784\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0809 - acc: 0.9673\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0584 - acc: 0.9799\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0669 - acc: 0.9744\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0845 - acc: 0.9682\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0530 - acc: 0.9776\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0426 - acc: 0.9864\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0498 - acc: 0.9814\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0641 - acc: 0.9735\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0752 - acc: 0.9711\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0855 - acc: 0.9677\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0607 - acc: 0.9783\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0582 - acc: 0.9784\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1700 - acc: 0.9310\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1640 - acc: 0.9322\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1495 - acc: 0.9401\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1741 - acc: 0.9255\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1468 - acc: 0.9401\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1430 - acc: 0.9418\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1356 - acc: 0.9453\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1531 - acc: 0.9355\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1362 - acc: 0.9421\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 10/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1374 - acc: 0.9453\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1391 - acc: 0.9443\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1255 - acc: 0.9501\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1428 - acc: 0.9394\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1322 - acc: 0.9484\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1372 - acc: 0.9449\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1194 - acc: 0.9527\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1246 - acc: 0.9504\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1148 - acc: 0.9542\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1044 - acc: 0.9572\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1005 - acc: 0.9622\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0940 - acc: 0.9633\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1006 - acc: 0.9572\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0937 - acc: 0.9615\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1241 - acc: 0.9493\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0937 - acc: 0.9636\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1215 - acc: 0.9493\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0960 - acc: 0.9621\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0971 - acc: 0.9611\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0959 - acc: 0.9622\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0878 - acc: 0.9662\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0872 - acc: 0.9678\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1014 - acc: 0.9619\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1318 - acc: 0.9453\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0793 - acc: 0.9698\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0794 - acc: 0.9691\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0779 - acc: 0.9702\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0566 - acc: 0.9783\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 44us/step - loss: 0.0873 - acc: 0.9652\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.1111 - acc: 0.9556\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0741 - acc: 0.9704\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0710 - acc: 0.9714\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0763 - acc: 0.9718\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0617 - acc: 0.9759\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0694 - acc: 0.9737\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0631 - acc: 0.9766\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0670 - acc: 0.9724\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0625 - acc: 0.9762\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0929 - acc: 0.9627\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0759 - acc: 0.9677\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0759 - acc: 0.9717\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1375 - acc: 0.9439\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1329 - acc: 0.9458\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1493 - acc: 0.9388\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1343 - acc: 0.9451\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1205 - acc: 0.9539\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1202 - acc: 0.9513\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.1416 - acc: 0.9457\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1177 - acc: 0.9556\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1208 - acc: 0.9513\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1152 - acc: 0.9511\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.1203 - acc: 0.9501\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0965 - acc: 0.9636\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1149 - acc: 0.9553\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0974 - acc: 0.9604\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1122 - acc: 0.9546\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1106 - acc: 0.9556\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.1113 - acc: 0.9556\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1064 - acc: 0.9585\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0908 - acc: 0.9630\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0831 - acc: 0.9678\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1106 - acc: 0.9559\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0847 - acc: 0.9663\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0775 - acc: 0.9691\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0801 - acc: 0.9662\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0790 - acc: 0.9693\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1036 - acc: 0.9596\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0682 - acc: 0.9726\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0756 - acc: 0.9711\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0810 - acc: 0.9655\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0709 - acc: 0.9732\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1054 - acc: 0.9592\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0654 - acc: 0.9740\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0455 - acc: 0.9841\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0616 - acc: 0.9757\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1209 - acc: 0.9557\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0545 - acc: 0.9799\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0535 - acc: 0.9805\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0789 - acc: 0.9700\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0665 - acc: 0.9736\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0639 - acc: 0.9746\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.0636 - acc: 0.9739\n", "Epoch 42/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 42us/step - loss: 0.0630 - acc: 0.9775\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0525 - acc: 0.9788\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0597 - acc: 0.9764\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.1199 - acc: 0.9556\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0513 - acc: 0.9799\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.0477 - acc: 0.9817\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.0545 - acc: 0.9772\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0456 - acc: 0.9820\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.0428 - acc: 0.9827\n", " 0.9118128812233374\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1509 - acc: 0.9409\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1429 - acc: 0.9442\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1315 - acc: 0.9467\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1519 - acc: 0.9379\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1211 - acc: 0.9509\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.1304 - acc: 0.9475\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1276 - acc: 0.9461\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1273 - acc: 0.9453\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.1201 - acc: 0.9509\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1349 - acc: 0.9453\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0936 - acc: 0.9643\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1067 - acc: 0.9573\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1147 - acc: 0.9538\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1409 - acc: 0.9460\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0994 - acc: 0.9600\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0937 - acc: 0.9619\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1036 - acc: 0.9566\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0866 - acc: 0.9670\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0855 - acc: 0.9665\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0758 - acc: 0.9688\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1011 - acc: 0.9593\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1174 - acc: 0.9518\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0710 - acc: 0.9724\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0651 - acc: 0.9750\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.0661 - acc: 0.9743\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1052 - acc: 0.9588\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0932 - acc: 0.9608\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0659 - acc: 0.9737\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0635 - acc: 0.9754\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0729 - acc: 0.9700\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0726 - acc: 0.9706\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0566 - acc: 0.9786\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0628 - acc: 0.9747\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0702 - acc: 0.9703\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1084 - acc: 0.9588\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1039 - acc: 0.9595\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0552 - acc: 0.9775\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0608 - acc: 0.9764\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0848 - acc: 0.9665\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0476 - acc: 0.9823\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0467 - acc: 0.9799\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0555 - acc: 0.9788\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0688 - acc: 0.9729\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0544 - acc: 0.9786\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0588 - acc: 0.9758\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0539 - acc: 0.9780\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0549 - acc: 0.9775\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0705 - acc: 0.9722\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0800 - acc: 0.9685\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0634 - acc: 0.9761\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1633 - acc: 0.9357\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1798 - acc: 0.9265\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1584 - acc: 0.9375\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1656 - acc: 0.9313\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1515 - acc: 0.9414\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1500 - acc: 0.9414\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1615 - acc: 0.9346\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1483 - acc: 0.9397\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1382 - acc: 0.9430\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1577 - acc: 0.9351\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1389 - acc: 0.9428\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1329 - acc: 0.9467\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1475 - acc: 0.9398\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1416 - acc: 0.9428\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1294 - acc: 0.9487\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1217 - acc: 0.9500\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1419 - acc: 0.9420\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1334 - acc: 0.9449\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1061 - acc: 0.9590\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1340 - acc: 0.9449\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1332 - acc: 0.9465\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1154 - acc: 0.9544\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1006 - acc: 0.9590\n", "Epoch 24/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 40us/step - loss: 0.1222 - acc: 0.9501\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1088 - acc: 0.9567\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1037 - acc: 0.9607\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0911 - acc: 0.9615\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0897 - acc: 0.9630\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1131 - acc: 0.9566\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1197 - acc: 0.9529\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0837 - acc: 0.9674\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0964 - acc: 0.9614\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0988 - acc: 0.9597\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0922 - acc: 0.9637\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1056 - acc: 0.9579\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0901 - acc: 0.9638\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1140 - acc: 0.9552\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0950 - acc: 0.9604\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0868 - acc: 0.9645\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0671 - acc: 0.9740\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0790 - acc: 0.9698\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0943 - acc: 0.9615\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0924 - acc: 0.9636\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0887 - acc: 0.9641\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0833 - acc: 0.9663\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0875 - acc: 0.9640\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0670 - acc: 0.9751\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1023 - acc: 0.9615\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0869 - acc: 0.9659\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0676 - acc: 0.9710\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1610 - acc: 0.9362\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1530 - acc: 0.9359\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1330 - acc: 0.9471\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1536 - acc: 0.9405\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1764 - acc: 0.9256\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1411 - acc: 0.9446\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1335 - acc: 0.9464\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1458 - acc: 0.9384\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1218 - acc: 0.9482\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1146 - acc: 0.9564\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1353 - acc: 0.9442\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1264 - acc: 0.9502\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1261 - acc: 0.9468\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1083 - acc: 0.9589\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 64us/step - loss: 0.1052 - acc: 0.9578\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 64us/step - loss: 0.1181 - acc: 0.9531\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 55us/step - loss: 0.1025 - acc: 0.9590\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 61us/step - loss: 0.1133 - acc: 0.9552\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 57us/step - loss: 0.1004 - acc: 0.9585\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 56us/step - loss: 0.0962 - acc: 0.9630\n", "Epoch 21/50\n", "7275/7275 [==============================] - 1s 103us/step - loss: 0.1019 - acc: 0.9592\n", "Epoch 22/50\n", "7275/7275 [==============================] - 1s 79us/step - loss: 0.0993 - acc: 0.9604\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0923 - acc: 0.9659\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 55us/step - loss: 0.0963 - acc: 0.9612\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0975 - acc: 0.9614\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0860 - acc: 0.9648\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 55us/step - loss: 0.0931 - acc: 0.9652\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0831 - acc: 0.9638\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1039 - acc: 0.9562\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0686 - acc: 0.9726\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1223 - acc: 0.9491\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 60us/step - loss: 0.0839 - acc: 0.9665\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 52us/step - loss: 0.0808 - acc: 0.9670\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0715 - acc: 0.9709\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0897 - acc: 0.9641\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0755 - acc: 0.9713\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0733 - acc: 0.9713\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0670 - acc: 0.9750\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0926 - acc: 0.9636\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0913 - acc: 0.9627\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0647 - acc: 0.9739\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0933 - acc: 0.9629\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0581 - acc: 0.9769\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0513 - acc: 0.9816\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0531 - acc: 0.9805\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.0497 - acc: 0.9808\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0535 - acc: 0.9783\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0951 - acc: 0.9625\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0570 - acc: 0.9768\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0666 - acc: 0.9743\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1734 - acc: 0.9310\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1484 - acc: 0.9386\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1561 - acc: 0.9375\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1470 - acc: 0.9395\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1607 - acc: 0.9331\n", "Epoch 6/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 40us/step - loss: 0.1435 - acc: 0.9408\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1298 - acc: 0.9469\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1487 - acc: 0.9366\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1270 - acc: 0.9512\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1288 - acc: 0.9452\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1270 - acc: 0.9485\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1381 - acc: 0.9416\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1261 - acc: 0.9471\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1496 - acc: 0.9394\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1256 - acc: 0.9491\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1083 - acc: 0.9578\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1086 - acc: 0.9541\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1145 - acc: 0.9560\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1087 - acc: 0.9586\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0991 - acc: 0.9604\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1024 - acc: 0.9595\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1054 - acc: 0.9579\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1305 - acc: 0.9461\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1002 - acc: 0.9584\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0803 - acc: 0.9680\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0977 - acc: 0.9608\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1048 - acc: 0.9586\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0833 - acc: 0.9667\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0873 - acc: 0.9656\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1024 - acc: 0.9584\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1047 - acc: 0.9582\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0878 - acc: 0.9649\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0764 - acc: 0.9707\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0789 - acc: 0.9688\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0824 - acc: 0.9676\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0760 - acc: 0.9687\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1192 - acc: 0.9519\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0809 - acc: 0.9673\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0901 - acc: 0.9644\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0728 - acc: 0.9710\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0683 - acc: 0.9724\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0942 - acc: 0.9623\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0880 - acc: 0.9667\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0631 - acc: 0.9764\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0632 - acc: 0.9729\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0639 - acc: 0.9731\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0669 - acc: 0.9744\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0692 - acc: 0.9726\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0704 - acc: 0.9728\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0916 - acc: 0.9614\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 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[==============================] - 0s 42us/step - loss: 0.1324 - acc: 0.9456\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1313 - acc: 0.9482\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1368 - acc: 0.9409\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1133 - acc: 0.9551\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1066 - acc: 0.9563\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1362 - acc: 0.9457\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0970 - acc: 0.9595\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0974 - acc: 0.9632\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1125 - acc: 0.9533\n", "Epoch 19/50\n", "7275/7275 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[==============================] - 0s 46us/step - loss: 0.0819 - acc: 0.9665\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0783 - acc: 0.9710\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 39/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0595 - acc: 0.9750\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0619 - acc: 0.9757\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0602 - acc: 0.9757\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0819 - acc: 0.9689\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 64us/step - loss: 0.1201 - acc: 0.9546\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0676 - acc: 0.9742\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0526 - acc: 0.9801\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0517 - acc: 0.9780\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 56us/step - loss: 0.0499 - acc: 0.9809\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 54us/step - loss: 0.0549 - acc: 0.9766\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 65us/step - loss: 0.0565 - acc: 0.9783\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0515 - acc: 0.9802\n", " 0.8950230375217507\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1588 - acc: 0.9355\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1604 - acc: 0.9350\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1448 - acc: 0.9410\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1357 - acc: 0.9461\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1509 - acc: 0.9376\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1329 - acc: 0.9461\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1319 - acc: 0.9471\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1360 - acc: 0.9431\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1343 - acc: 0.9472\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1100 - acc: 0.9556\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1182 - acc: 0.9513\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1164 - acc: 0.9520\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1168 - acc: 0.9507\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1276 - acc: 0.9471\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1132 - acc: 0.9537\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1330 - acc: 0.9469\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1108 - acc: 0.9559\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0870 - acc: 0.9669\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1310 - acc: 0.9446\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1054 - acc: 0.9559\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0905 - acc: 0.9634\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0864 - acc: 0.9656\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1016 - acc: 0.9595\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0880 - acc: 0.9673\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0864 - acc: 0.9659\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0998 - acc: 0.9585\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0831 - acc: 0.9674\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0843 - acc: 0.9656\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0857 - acc: 0.9663\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0922 - acc: 0.9626\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1136 - acc: 0.9549\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0667 - acc: 0.9753\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0783 - acc: 0.9682\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0678 - acc: 0.9726\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0540 - acc: 0.9786\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0670 - acc: 0.9733\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0871 - acc: 0.9669\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0973 - acc: 0.9641\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0650 - acc: 0.9742\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0911 - acc: 0.9633\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0646 - acc: 0.9747\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0656 - acc: 0.9748\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0512 - acc: 0.9792\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0693 - acc: 0.9703\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0756 - acc: 0.9714\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0618 - acc: 0.9758\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0622 - acc: 0.9765\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0483 - acc: 0.9830\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0643 - acc: 0.9757\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0588 - acc: 0.9766\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1686 - acc: 0.9303\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1629 - acc: 0.9326\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1656 - acc: 0.9296\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1816 - acc: 0.9238\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1617 - acc: 0.9350\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1583 - acc: 0.9351\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1498 - acc: 0.9381\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1544 - acc: 0.9364\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 56us/step - loss: 0.1376 - acc: 0.9409\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 52us/step - loss: 0.1358 - acc: 0.9472\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1510 - acc: 0.9375\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1395 - acc: 0.9412\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1315 - acc: 0.9490\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 52us/step - loss: 0.1272 - acc: 0.9452\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1515 - acc: 0.9383\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1185 - acc: 0.9518\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1298 - acc: 0.9474\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1049 - acc: 0.9581\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1099 - acc: 0.9546\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.1196 - acc: 0.9533\n", "Epoch 21/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 67us/step - loss: 0.1130 - acc: 0.9553\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 66us/step - loss: 0.1278 - acc: 0.9456\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 58us/step - loss: 0.1073 - acc: 0.9546\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1088 - acc: 0.9527\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0984 - acc: 0.9622\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 58us/step - loss: 0.1078 - acc: 0.9571\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 54us/step - loss: 0.0970 - acc: 0.9616\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 62us/step - loss: 0.0990 - acc: 0.9588\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1133 - acc: 0.9548\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0910 - acc: 0.9627\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0979 - acc: 0.9595\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1047 - acc: 0.9566\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0793 - acc: 0.9702\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0748 - acc: 0.9715\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0873 - acc: 0.9644\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1029 - acc: 0.9596\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 57us/step - loss: 0.0751 - acc: 0.9704\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.1042 - acc: 0.9584\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1029 - acc: 0.9593\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0774 - acc: 0.9713\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0800 - acc: 0.9665\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0889 - acc: 0.9645\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0679 - acc: 0.9724\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0860 - acc: 0.9641\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 63us/step - loss: 0.1057 - acc: 0.9592\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.0827 - acc: 0.9667\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0870 - acc: 0.9648\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0665 - acc: 0.9739\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0632 - acc: 0.9748\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0634 - acc: 0.9751\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1496 - acc: 0.9395\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1487 - acc: 0.9395\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1440 - acc: 0.9432\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1353 - acc: 0.9458\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1484 - acc: 0.9381\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1344 - acc: 0.9446\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1286 - acc: 0.9493\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1429 - acc: 0.9401\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1342 - acc: 0.9450\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1333 - acc: 0.9457\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1121 - acc: 0.9540\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1183 - acc: 0.9522\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1056 - acc: 0.9578\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1013 - acc: 0.9593\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1066 - acc: 0.9579\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1167 - acc: 0.9541\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1162 - acc: 0.9551\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1137 - acc: 0.9529\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0893 - acc: 0.9633\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0895 - acc: 0.9605\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0949 - acc: 0.9610\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0933 - acc: 0.9607\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0784 - acc: 0.9689\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1201 - acc: 0.9530\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1060 - acc: 0.9571\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0931 - acc: 0.9656\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0768 - acc: 0.9682\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1082 - acc: 0.9574\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0932 - acc: 0.9621\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0738 - acc: 0.9714\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0648 - acc: 0.9736\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0893 - acc: 0.9641\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0753 - acc: 0.9696\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0703 - acc: 0.9725\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0610 - acc: 0.9772\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0931 - acc: 0.9627\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0551 - acc: 0.9790\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0556 - acc: 0.9766\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1042 - acc: 0.9600\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0721 - acc: 0.9724\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0601 - acc: 0.9768\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0946 - acc: 0.9627\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0682 - acc: 0.9742\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0529 - acc: 0.9797\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0593 - acc: 0.9755\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0605 - acc: 0.9761\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0581 - acc: 0.9773\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0626 - acc: 0.9748\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0431 - acc: 0.9836\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0709 - acc: 0.9720\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1780 - acc: 0.9284\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1804 - acc: 0.9251\n", "Epoch 3/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 41us/step - loss: 0.1639 - acc: 0.9314\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1576 - acc: 0.9368\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1623 - acc: 0.9354\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1479 - acc: 0.9383\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1560 - acc: 0.9346\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1412 - acc: 0.9425\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1618 - acc: 0.9288\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1476 - acc: 0.9380\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1392 - acc: 0.9436\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1527 - acc: 0.9372\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1344 - acc: 0.9446\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1369 - acc: 0.9427\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1291 - acc: 0.9478\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1783 - acc: 0.9270\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1215 - acc: 0.9526\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1199 - acc: 0.9476\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1287 - acc: 0.9500\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1165 - acc: 0.9512\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1195 - acc: 0.9493\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1153 - acc: 0.9518\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1110 - acc: 0.9557\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1163 - acc: 0.9515\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1151 - acc: 0.9531\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1181 - acc: 0.9512\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1184 - acc: 0.9512\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0960 - acc: 0.9612\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1163 - acc: 0.9515\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1002 - acc: 0.9612\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1167 - acc: 0.9531\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1000 - acc: 0.9605\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0938 - acc: 0.9621\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0978 - acc: 0.9625\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0935 - acc: 0.9626\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0999 - acc: 0.9585\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1147 - acc: 0.9538\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0989 - acc: 0.9567\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0984 - acc: 0.9596\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0949 - acc: 0.9614\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0727 - acc: 0.9728\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0804 - acc: 0.9663\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0956 - acc: 0.9586\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0800 - acc: 0.9678\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0664 - acc: 0.9737\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0869 - acc: 0.9656\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0707 - acc: 0.9726\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0887 - acc: 0.9643\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0769 - acc: 0.9693\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0649 - acc: 0.9757\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1411 - acc: 0.9434\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1562 - acc: 0.9355\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1347 - acc: 0.9452\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1405 - acc: 0.9391\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1538 - acc: 0.9321\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1231 - acc: 0.9489\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1243 - acc: 0.9509\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1154 - acc: 0.9529\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1245 - acc: 0.9469\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1421 - acc: 0.9438\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1125 - acc: 0.9534\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1247 - acc: 0.9487\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1225 - acc: 0.9496\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0984 - acc: 0.9600\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1145 - acc: 0.9542\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1085 - acc: 0.9570\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0842 - acc: 0.9669\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0980 - acc: 0.9612\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1146 - acc: 0.9538\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1044 - acc: 0.9560\n", "Epoch 21/50\n", "7275/7275 [==============================] - 1s 86us/step - loss: 0.1003 - acc: 0.9588\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0842 - acc: 0.9652\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0887 - acc: 0.9630\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0783 - acc: 0.9685\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1142 - acc: 0.9519\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0806 - acc: 0.9693\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1065 - acc: 0.9581\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0854 - acc: 0.9674\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0977 - acc: 0.9597\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0874 - acc: 0.9660\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0731 - acc: 0.9703\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0874 - acc: 0.9666\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0623 - acc: 0.9772\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0783 - acc: 0.9693\n", "Epoch 35/50\n", "7275/7275 [==============================] - 1s 77us/step - loss: 0.0729 - acc: 0.9715\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 36/50\n", "7275/7275 [==============================] - 0s 61us/step - loss: 0.0893 - acc: 0.9659\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0854 - acc: 0.9665\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0656 - acc: 0.9724\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0656 - acc: 0.9754\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0621 - acc: 0.9750\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0511 - acc: 0.9805\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0748 - acc: 0.9709\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 57us/step - loss: 0.0534 - acc: 0.9792\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0573 - acc: 0.9759\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0591 - acc: 0.9773\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0550 - acc: 0.9780\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0559 - acc: 0.9780\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0552 - acc: 0.9791\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0821 - acc: 0.9680\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.0792 - acc: 0.9684\n", " 0.9104416341935643\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1479 - acc: 0.9373\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1528 - acc: 0.9357\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1386 - acc: 0.9419\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1406 - acc: 0.9405\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1548 - acc: 0.9375\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1374 - acc: 0.9427\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1283 - acc: 0.9471\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1290 - acc: 0.9463\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1169 - acc: 0.9530\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1271 - acc: 0.9456\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1290 - acc: 0.9487\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1134 - acc: 0.9577\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1377 - acc: 0.9441\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1067 - acc: 0.9601\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1109 - acc: 0.9566\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1053 - acc: 0.9584\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1128 - acc: 0.9538\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0945 - acc: 0.9621\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1205 - acc: 0.9505\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0911 - acc: 0.9625\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0896 - acc: 0.9660\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1182 - acc: 0.9524\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0863 - acc: 0.9644\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0825 - acc: 0.9667\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1085 - acc: 0.9568\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0941 - acc: 0.9622\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0891 - acc: 0.9648\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0810 - acc: 0.9691\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0760 - acc: 0.9714\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0792 - acc: 0.9673\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0748 - acc: 0.9706\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0973 - acc: 0.9607\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0796 - acc: 0.9704\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0681 - acc: 0.9735\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0555 - acc: 0.9772\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0959 - acc: 0.9643\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1133 - acc: 0.9549\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0769 - acc: 0.9709\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0640 - acc: 0.9754\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0748 - acc: 0.9721\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0735 - acc: 0.9720\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0514 - acc: 0.9820\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0523 - acc: 0.9795\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0644 - acc: 0.9743\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0705 - acc: 0.9726\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0717 - acc: 0.9726\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1216 - acc: 0.9535\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0611 - acc: 0.9776\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0514 - acc: 0.9797\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0538 - acc: 0.9787\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.1733 - acc: 0.9287\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1637 - acc: 0.9322\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1675 - acc: 0.9302\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1482 - acc: 0.9377\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1504 - acc: 0.9403\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1664 - acc: 0.9307\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1421 - acc: 0.9405\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1485 - acc: 0.9383\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1457 - acc: 0.9416\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1391 - acc: 0.9441\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1366 - acc: 0.9421\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.1396 - acc: 0.9439\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.1166 - acc: 0.9524\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1108 - acc: 0.9570\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1138 - acc: 0.9507\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1460 - acc: 0.9377\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1592 - acc: 0.9328\n", "Epoch 18/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 44us/step - loss: 0.1246 - acc: 0.9460\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1169 - acc: 0.9519\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0965 - acc: 0.9619\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0992 - acc: 0.9616\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1210 - acc: 0.9502\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1086 - acc: 0.9560\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0843 - acc: 0.9652\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1108 - acc: 0.9531\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1000 - acc: 0.9586\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1064 - acc: 0.9567\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0784 - acc: 0.9691\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0864 - acc: 0.9673\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0923 - acc: 0.9644\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0993 - acc: 0.9599\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1009 - acc: 0.9577\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0849 - acc: 0.9640\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0839 - acc: 0.9662\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1024 - acc: 0.9586\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0741 - acc: 0.9699\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0843 - acc: 0.9670\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1113 - acc: 0.9555\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0888 - acc: 0.9647\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0727 - acc: 0.9718\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0925 - acc: 0.9640\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0915 - acc: 0.9626\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1175 - acc: 0.9575\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0579 - acc: 0.9770\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0623 - acc: 0.9751\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0722 - acc: 0.9702\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0788 - acc: 0.9685\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0687 - acc: 0.9729\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0763 - acc: 0.9699\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0675 - acc: 0.9746\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1455 - acc: 0.9434\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1508 - acc: 0.9376\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1551 - acc: 0.9366\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1370 - acc: 0.9445\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1333 - acc: 0.9485\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1370 - acc: 0.9461\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1436 - acc: 0.9408\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1352 - acc: 0.9460\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1399 - acc: 0.9405\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1109 - acc: 0.9567\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1220 - acc: 0.9511\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1408 - acc: 0.9447\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1002 - acc: 0.9619\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1135 - acc: 0.9549\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1065 - acc: 0.9557\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1116 - acc: 0.9542\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1032 - acc: 0.9608\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1294 - acc: 0.9483\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0991 - acc: 0.9595\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0858 - acc: 0.9658\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0948 - acc: 0.9608\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0898 - acc: 0.9644\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0935 - acc: 0.9643\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0757 - acc: 0.9695\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0764 - acc: 0.9728\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0860 - acc: 0.9678\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0896 - acc: 0.9630\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0913 - acc: 0.9647\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0825 - acc: 0.9677\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0902 - acc: 0.9645\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0830 - acc: 0.9655\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0826 - acc: 0.9685\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0825 - acc: 0.9682\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0896 - acc: 0.9662\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0681 - acc: 0.9750\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0761 - acc: 0.9715\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0920 - acc: 0.9643\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0825 - acc: 0.9676\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0712 - acc: 0.9714\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0718 - acc: 0.9718\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0732 - acc: 0.9713\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1000 - acc: 0.9610\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0661 - acc: 0.9747\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0693 - acc: 0.9726\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0618 - acc: 0.9764\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0961 - acc: 0.9603\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0543 - acc: 0.9799\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0468 - acc: 0.9810\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0465 - acc: 0.9828\n", "Epoch 50/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 42us/step - loss: 0.0543 - acc: 0.9781\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1539 - acc: 0.9368\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1506 - acc: 0.9401\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1448 - acc: 0.9442\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1503 - acc: 0.9395\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1481 - acc: 0.9416\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1424 - acc: 0.9403\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1259 - acc: 0.9485\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1433 - acc: 0.9435\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1362 - acc: 0.9445\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1250 - acc: 0.9486\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1255 - acc: 0.9490\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1144 - acc: 0.9555\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1246 - acc: 0.9529\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1189 - acc: 0.9516\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1077 - acc: 0.9586\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1072 - acc: 0.9592\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1017 - acc: 0.9590\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1092 - acc: 0.9566\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0964 - acc: 0.9589\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1044 - acc: 0.9571\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1025 - acc: 0.9611\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1024 - acc: 0.9618\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1023 - acc: 0.9575\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0993 - acc: 0.9616\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0811 - acc: 0.9678\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0929 - acc: 0.9622\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1138 - acc: 0.9513\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0916 - acc: 0.9625\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0953 - acc: 0.9601\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0933 - acc: 0.9625\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1021 - acc: 0.9604\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0798 - acc: 0.9685\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0685 - acc: 0.9720\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0755 - acc: 0.9688\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0897 - acc: 0.9649\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0860 - acc: 0.9658\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0787 - acc: 0.9676: 0s - loss: 0.0601 - acc: 0\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0635 - acc: 0.9758\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0883 - acc: 0.9677\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0768 - acc: 0.9687\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0683 - acc: 0.9729\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0818 - acc: 0.9684\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0614 - acc: 0.9753\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0790 - acc: 0.9687\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0730 - acc: 0.9733\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0665 - acc: 0.9737\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0701 - acc: 0.9715\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0716 - acc: 0.9732\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0762 - acc: 0.9707\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0580 - acc: 0.9772\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1571 - acc: 0.9364\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1510 - acc: 0.9381\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1315 - acc: 0.9471\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1446 - acc: 0.9383\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1566 - acc: 0.9342\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1326 - acc: 0.9471\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1382 - acc: 0.9438\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1307 - acc: 0.9449\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1272 - acc: 0.9457\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1257 - acc: 0.9508\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1529 - acc: 0.9383\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1168 - acc: 0.9533\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1093 - acc: 0.9563\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1204 - acc: 0.9513\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1240 - acc: 0.9490\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1012 - acc: 0.9603\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1102 - acc: 0.9579\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0916 - acc: 0.9636\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1045 - acc: 0.9557\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0995 - acc: 0.9597\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1050 - acc: 0.9589\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0815 - acc: 0.9666\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0925 - acc: 0.9648\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0822 - acc: 0.9687\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0838 - acc: 0.9677\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0903 - acc: 0.9629\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0835 - acc: 0.9647\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0920 - acc: 0.9629\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0818 - acc: 0.9671\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1006 - acc: 0.9575\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1305 - acc: 0.9498\n", "Epoch 32/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 43us/step - loss: 0.1291 - acc: 0.9461\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0734 - acc: 0.9707\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0576 - acc: 0.9775\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0959 - acc: 0.9612\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1142 - acc: 0.9540\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0691 - acc: 0.9737\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0531 - acc: 0.9805\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0591 - acc: 0.9758\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0583 - acc: 0.9790\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0640 - acc: 0.9746\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0621 - acc: 0.9759\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0714 - acc: 0.9736\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1392 - acc: 0.9485\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0642 - acc: 0.9740\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0510 - acc: 0.9792\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0753 - acc: 0.9709\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0764 - acc: 0.9695\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0555 - acc: 0.9781\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0852 - acc: 0.9649\n", " 0.915569933583315\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1621 - acc: 0.9321\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1643 - acc: 0.9306\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1582 - acc: 0.9337\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1614 - acc: 0.9325\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1423 - acc: 0.9436\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1439 - acc: 0.9413\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1570 - acc: 0.9362\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1431 - acc: 0.9410\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1573 - acc: 0.9346\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1333 - acc: 0.9441\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1404 - acc: 0.9421\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1357 - acc: 0.9457\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1279 - acc: 0.9450\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1231 - acc: 0.9509\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1213 - acc: 0.9522\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1255 - acc: 0.9498\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1220 - acc: 0.9479\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1299 - acc: 0.9456\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1356 - acc: 0.9456\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1091 - acc: 0.9563\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1170 - acc: 0.9508\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1070 - acc: 0.9590\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0967 - acc: 0.9618\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1063 - acc: 0.9573\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1062 - acc: 0.9589\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1168 - acc: 0.9500\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1430 - acc: 0.9425\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0848 - acc: 0.9660\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0965 - acc: 0.9616\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1151 - acc: 0.9516\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0863 - acc: 0.9637\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1030 - acc: 0.9568\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0904 - acc: 0.9651\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1006 - acc: 0.9589\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0866 - acc: 0.9645\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0901 - acc: 0.9660\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0826 - acc: 0.9684\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0951 - acc: 0.9649\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0957 - acc: 0.9619\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0782 - acc: 0.9689\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0948 - acc: 0.9595\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0764 - acc: 0.9699\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0776 - acc: 0.9696\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0688 - acc: 0.9726\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0670 - acc: 0.9733\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0873 - acc: 0.9634\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0800 - acc: 0.9667\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0849 - acc: 0.9656\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0719 - acc: 0.9717\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0700 - acc: 0.9720\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1542 - acc: 0.9365\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1508 - acc: 0.9373\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1499 - acc: 0.9401\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1719 - acc: 0.9299\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1363 - acc: 0.9428\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1325 - acc: 0.9438\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1546 - acc: 0.9372\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1302 - acc: 0.9489\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1364 - acc: 0.9463\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1363 - acc: 0.9436\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1295 - acc: 0.9498\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1211 - acc: 0.9516\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1271 - acc: 0.9461\n", "Epoch 14/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 41us/step - loss: 0.1147 - acc: 0.9552\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1159 - acc: 0.9540\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1193 - acc: 0.9497\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1192 - acc: 0.9523\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1133 - acc: 0.9538\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1175 - acc: 0.9531\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1046 - acc: 0.9551\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1043 - acc: 0.9585\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1011 - acc: 0.9601\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0977 - acc: 0.9625\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0957 - acc: 0.9625\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0943 - acc: 0.9622\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0859 - acc: 0.9640\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0915 - acc: 0.9610\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0890 - acc: 0.9651\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0785 - acc: 0.9684\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0946 - acc: 0.9637\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0894 - acc: 0.9649\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0855 - acc: 0.9663\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0846 - acc: 0.9671\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0783 - acc: 0.9692\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1041 - acc: 0.9578\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0865 - acc: 0.9643\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0777 - acc: 0.9691\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0904 - acc: 0.9637\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0787 - acc: 0.9674\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0577 - acc: 0.9788\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0898 - acc: 0.9659\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0941 - acc: 0.9629\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0727 - acc: 0.9725\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0664 - acc: 0.9747\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0619 - acc: 0.9759\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0774 - acc: 0.9713\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1073 - acc: 0.9556\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0679 - acc: 0.9729\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0784 - acc: 0.9673\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0525 - acc: 0.9791\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1546 - acc: 0.9348\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1580 - acc: 0.9348\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1597 - acc: 0.9332\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1519 - acc: 0.9365\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1589 - acc: 0.9340\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1296 - acc: 0.9457\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1382 - acc: 0.9468\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1393 - acc: 0.9436\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1638 - acc: 0.9321\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1391 - acc: 0.9412\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1471 - acc: 0.9384\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1335 - acc: 0.9469\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1168 - acc: 0.9541\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1121 - acc: 0.9567\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1158 - acc: 0.9566\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1487 - acc: 0.9395\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1201 - acc: 0.9523\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1460 - acc: 0.9431\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1341 - acc: 0.9465\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1144 - acc: 0.9526\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1118 - acc: 0.9529\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1014 - acc: 0.9597\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0997 - acc: 0.9616\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1030 - acc: 0.9567\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0894 - acc: 0.9619\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0917 - acc: 0.9656\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0894 - acc: 0.9638\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0903 - acc: 0.9626\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0810 - acc: 0.9662\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1057 - acc: 0.9555\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0840 - acc: 0.9660\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0792 - acc: 0.9693\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1009 - acc: 0.9582\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1082 - acc: 0.9567\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0970 - acc: 0.9636\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0656 - acc: 0.9742\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1124 - acc: 0.9553\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0661 - acc: 0.9729\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0725 - acc: 0.9720\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0759 - acc: 0.9709\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0749 - acc: 0.9698\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0760 - acc: 0.9700\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0611 - acc: 0.9739\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0721 - acc: 0.9695\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0805 - acc: 0.9677\n", "Epoch 46/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 43us/step - loss: 0.0909 - acc: 0.9649\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0702 - acc: 0.9706\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0787 - acc: 0.9691\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0655 - acc: 0.9735\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1003 - acc: 0.9604\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1575 - acc: 0.9359\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1415 - acc: 0.9446\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1341 - acc: 0.9453\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1469 - acc: 0.9399\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1337 - acc: 0.9450\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1268 - acc: 0.9469\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1327 - acc: 0.9464\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1298 - acc: 0.9464\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1079 - acc: 0.9579\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1256 - acc: 0.9493\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1227 - acc: 0.9491\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1075 - acc: 0.9551\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1154 - acc: 0.9546\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1008 - acc: 0.9578\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1030 - acc: 0.9571\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0990 - acc: 0.9584\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1063 - acc: 0.9571\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1192 - acc: 0.9531\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1383 - acc: 0.9420\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0851 - acc: 0.9666\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0909 - acc: 0.9632\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0933 - acc: 0.9622\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0873 - acc: 0.9658\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0795 - acc: 0.9685\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0928 - acc: 0.9640\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1133 - acc: 0.9540\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0718 - acc: 0.9707\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0661 - acc: 0.9743\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0777 - acc: 0.9682\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0674 - acc: 0.9715\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0799 - acc: 0.9678\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0918 - acc: 0.9612\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1042 - acc: 0.9621\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0841 - acc: 0.9644\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0668 - acc: 0.9718\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0759 - acc: 0.9696\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0548 - acc: 0.9765\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0791 - acc: 0.9649\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0691 - acc: 0.9711\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0771 - acc: 0.9699\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0516 - acc: 0.9783\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0737 - acc: 0.9698\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1258 - acc: 0.9519\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0577 - acc: 0.9772\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0455 - acc: 0.9824\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0795 - acc: 0.9666\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0662 - acc: 0.9742\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0425 - acc: 0.9842\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0545 - acc: 0.9786\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0410 - acc: 0.9821\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1579 - acc: 0.9300\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1548 - acc: 0.9362\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1603 - acc: 0.9326\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1592 - acc: 0.9343\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1525 - acc: 0.9344\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1571 - acc: 0.9336\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1585 - acc: 0.9320\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1689 - acc: 0.9273\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1445 - acc: 0.9384\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1359 - acc: 0.9436\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1320 - acc: 0.9460\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1351 - acc: 0.9421\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1234 - acc: 0.9489\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1302 - acc: 0.9467\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1224 - acc: 0.9500\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1325 - acc: 0.9461\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1185 - acc: 0.9509\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1308 - acc: 0.9450\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1224 - acc: 0.9496\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1076 - acc: 0.9541\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1094 - acc: 0.9523\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0976 - acc: 0.9600\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1106 - acc: 0.9524\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1101 - acc: 0.9556\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0906 - acc: 0.9633\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1083 - acc: 0.9549\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1144 - acc: 0.9501\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0909 - acc: 0.9633\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0801 - acc: 0.9681\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1068 - acc: 0.9566\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1052 - acc: 0.9585\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0881 - acc: 0.9649\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0881 - acc: 0.9652\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0954 - acc: 0.9607\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0797 - acc: 0.9706\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1059 - acc: 0.9579\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0931 - acc: 0.9627\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0729 - acc: 0.9714\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0841 - acc: 0.9658\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0854 - acc: 0.9645\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0806 - acc: 0.9676\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0671 - acc: 0.9722\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0708 - acc: 0.9695\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0928 - acc: 0.9616\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0740 - acc: 0.9707\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1002 - acc: 0.9615\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0673 - acc: 0.9715\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0717 - acc: 0.9702\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0487 - acc: 0.9817\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0681 - acc: 0.9746\n", " 0.916289856138029\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1422 - acc: 0.9431\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1327 - acc: 0.9478\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1435 - acc: 0.9413\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1320 - acc: 0.9445\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1441 - acc: 0.9419\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1172 - acc: 0.9545\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1450 - acc: 0.9419\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1378 - acc: 0.9432\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1090 - acc: 0.9560\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1064 - acc: 0.9568\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1065 - acc: 0.9582\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1063 - acc: 0.9581\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1048 - acc: 0.9553\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1094 - acc: 0.9586\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0864 - acc: 0.9662\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1056 - acc: 0.9557\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0985 - acc: 0.9614\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0865 - acc: 0.9662\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0887 - acc: 0.9643\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1111 - acc: 0.9567\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0822 - acc: 0.9667\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0893 - acc: 0.9662\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1028 - acc: 0.9586\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0950 - acc: 0.9618\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0813 - acc: 0.9663\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0782 - acc: 0.9691\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0748 - acc: 0.9725\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0749 - acc: 0.9722\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0887 - acc: 0.9665\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0929 - acc: 0.9634\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0802 - acc: 0.9699\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0754 - acc: 0.9673\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0739 - acc: 0.9744\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0564 - acc: 0.9781\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0671 - acc: 0.9744\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1096 - acc: 0.9578\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0693 - acc: 0.9743\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0768 - acc: 0.9709\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0559 - acc: 0.9799\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0564 - acc: 0.9777\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0821 - acc: 0.9674\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0959 - acc: 0.9633\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0941 - acc: 0.9659\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0580 - acc: 0.9770\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0735 - acc: 0.9729\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0574 - acc: 0.9795\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0469 - acc: 0.9814\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0681 - acc: 0.9751\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0441 - acc: 0.9830\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0477 - acc: 0.9806\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1763 - acc: 0.9304\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1579 - acc: 0.9348\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1400 - acc: 0.9449\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1356 - acc: 0.9442\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1546 - acc: 0.9343\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1864 - acc: 0.9233\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1671 - acc: 0.9315\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1359 - acc: 0.9456\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1529 - acc: 0.9354\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1405 - acc: 0.9445\n", "Epoch 11/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 41us/step - loss: 0.1307 - acc: 0.9461\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1338 - acc: 0.9458\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1213 - acc: 0.9500\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1062 - acc: 0.9564\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1193 - acc: 0.9491\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1236 - acc: 0.9504\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1338 - acc: 0.9469\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1196 - acc: 0.9508\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1211 - acc: 0.9504\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1222 - acc: 0.9512\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1220 - acc: 0.9524\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0912 - acc: 0.9643\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1076 - acc: 0.9552\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1166 - acc: 0.9545\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1087 - acc: 0.9562\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1096 - acc: 0.9563\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1013 - acc: 0.9599\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0976 - acc: 0.9605\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1048 - acc: 0.9579\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0820 - acc: 0.9669\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0975 - acc: 0.9621\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0900 - acc: 0.9649\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1190 - acc: 0.9507\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0836 - acc: 0.9670\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0892 - acc: 0.9636\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0773 - acc: 0.9685\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0740 - acc: 0.9720\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0809 - acc: 0.9667\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1014 - acc: 0.9590\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0851 - acc: 0.9654\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0634 - acc: 0.9754\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0867 - acc: 0.9667\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0673 - acc: 0.9720\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0754 - acc: 0.9680\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0818 - acc: 0.9648\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0736 - acc: 0.9682\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0818 - acc: 0.9714\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0649 - acc: 0.9742\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0788 - acc: 0.9687\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0687 - acc: 0.9737\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1579 - acc: 0.9350\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1582 - acc: 0.9339\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1624 - acc: 0.9302\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1527 - acc: 0.9390\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1433 - acc: 0.9377\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1419 - acc: 0.9423\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1458 - acc: 0.9386\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1500 - acc: 0.9386\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1402 - acc: 0.9435\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1394 - acc: 0.9449\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1316 - acc: 0.9460\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1251 - acc: 0.9469\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1305 - acc: 0.9469\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1226 - acc: 0.9494\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1145 - acc: 0.9522\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1197 - acc: 0.9513\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1177 - acc: 0.9533\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1236 - acc: 0.9507\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1109 - acc: 0.9564\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1068 - acc: 0.9553\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1207 - acc: 0.9511\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1016 - acc: 0.9599\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0948 - acc: 0.9619\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1130 - acc: 0.9544\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0908 - acc: 0.9621\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0901 - acc: 0.9632\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1144 - acc: 0.9545\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0871 - acc: 0.9634\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0830 - acc: 0.9693\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1167 - acc: 0.9527\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0923 - acc: 0.9636\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0791 - acc: 0.9703\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0849 - acc: 0.9671\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0832 - acc: 0.9651\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0720 - acc: 0.9715\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0923 - acc: 0.9638\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0917 - acc: 0.9634\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0794 - acc: 0.9682\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0605 - acc: 0.9776\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0716 - acc: 0.9704\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0691 - acc: 0.9721\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0855 - acc: 0.9656\n", "Epoch 43/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 40us/step - loss: 0.0891 - acc: 0.9652\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0517 - acc: 0.9795\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0553 - acc: 0.9810\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0616 - acc: 0.9757\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0680 - acc: 0.9731\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0609 - acc: 0.9775\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0560 - acc: 0.9775\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0786 - acc: 0.9662\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1429 - acc: 0.9409\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1341 - acc: 0.9431\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1282 - acc: 0.9468\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1564 - acc: 0.9342\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1240 - acc: 0.9504\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1293 - acc: 0.9463\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1328 - acc: 0.9432\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1479 - acc: 0.9377\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1268 - acc: 0.9468\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1276 - acc: 0.9465\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1204 - acc: 0.9478\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1047 - acc: 0.9595\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1184 - acc: 0.9502\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1151 - acc: 0.9519\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1257 - acc: 0.9494\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0950 - acc: 0.9610\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0872 - acc: 0.9640\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0825 - acc: 0.9667\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1128 - acc: 0.9548\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1396 - acc: 0.9388\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0865 - acc: 0.9644\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1156 - acc: 0.9538\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0997 - acc: 0.9586\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0752 - acc: 0.9709\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0871 - acc: 0.9636\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0954 - acc: 0.9601\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0921 - acc: 0.9626\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0956 - acc: 0.9625\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1029 - acc: 0.9597\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0829 - acc: 0.9648\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0770 - acc: 0.9696\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0786 - acc: 0.9648\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0795 - acc: 0.9698\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0678 - acc: 0.9721\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0991 - acc: 0.9596\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0727 - acc: 0.9733\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0813 - acc: 0.9663\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0737 - acc: 0.9704\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0724 - acc: 0.9703\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0653 - acc: 0.9757\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0513 - acc: 0.9805\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0445 - acc: 0.9817\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0830 - acc: 0.9678\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0602 - acc: 0.9765\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0514 - acc: 0.9801\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0772 - acc: 0.9698\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1232 - acc: 0.9494\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0750 - acc: 0.9704\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0566 - acc: 0.9776\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0511 - acc: 0.9802\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1463 - acc: 0.9401\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1446 - acc: 0.9394\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1540 - acc: 0.9346\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1531 - acc: 0.9348\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1119 - acc: 0.9529\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1505 - acc: 0.9394\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1469 - acc: 0.9408\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1167 - acc: 0.9537\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1145 - acc: 0.9522\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1090 - acc: 0.9557\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1217 - acc: 0.9529\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1191 - acc: 0.9522\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1039 - acc: 0.9582\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0910 - acc: 0.9616\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1098 - acc: 0.9573\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0952 - acc: 0.9634\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1041 - acc: 0.9581\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0856 - acc: 0.9666\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0942 - acc: 0.9638\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0873 - acc: 0.9665\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0992 - acc: 0.9614\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0918 - acc: 0.9638\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0813 - acc: 0.9685\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1005 - acc: 0.9577\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0861 - acc: 0.9654\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0739 - acc: 0.9714\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1010 - acc: 0.9599\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0731 - acc: 0.9714\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0783 - acc: 0.9687\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0712 - acc: 0.9709\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0718 - acc: 0.9681\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0798 - acc: 0.9681\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0659 - acc: 0.9755\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0749 - acc: 0.9704\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0896 - acc: 0.9641\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0627 - acc: 0.9761\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0575 - acc: 0.9779\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0736 - acc: 0.9703\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0700 - acc: 0.9724\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0713 - acc: 0.9725\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0541 - acc: 0.9797\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0516 - acc: 0.9806\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0592 - acc: 0.9776\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0936 - acc: 0.9626\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0554 - acc: 0.9779\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0417 - acc: 0.9839\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0477 - acc: 0.9824\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0548 - acc: 0.9790\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0467 - acc: 0.9823\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0670 - acc: 0.9735\n", " 0.9274226159841189\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1562 - acc: 0.9350\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1520 - acc: 0.9375\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1564 - acc: 0.9355\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1392 - acc: 0.9446\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.1461 - acc: 0.9414\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1359 - acc: 0.9439\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1337 - acc: 0.9431\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1301 - acc: 0.9464\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1212 - acc: 0.9471\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1402 - acc: 0.9452\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1213 - acc: 0.9513\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1406 - acc: 0.9427\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1141 - acc: 0.9564\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1067 - acc: 0.9586\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1199 - acc: 0.9538\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1142 - acc: 0.9533\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1015 - acc: 0.9610\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1181 - acc: 0.9523\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1156 - acc: 0.9511\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1082 - acc: 0.9541\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1152 - acc: 0.9542\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0941 - acc: 0.9619\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1076 - acc: 0.9566\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1063 - acc: 0.9567\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0963 - acc: 0.9627\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0804 - acc: 0.9684\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1065 - acc: 0.9557\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0886 - acc: 0.9651\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0911 - acc: 0.9644\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0943 - acc: 0.9636\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0979 - acc: 0.9616\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0706 - acc: 0.9737\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0641 - acc: 0.9761\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1170 - acc: 0.9531\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.0753 - acc: 0.9722\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0603 - acc: 0.9777\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0684 - acc: 0.9735\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0820 - acc: 0.9671\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0930 - acc: 0.9637\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0774 - acc: 0.9684\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0580 - acc: 0.9764\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0687 - acc: 0.9725\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0632 - acc: 0.9750\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0770 - acc: 0.9692\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0875 - acc: 0.9676\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0696 - acc: 0.9711\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0558 - acc: 0.9773\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0672 - acc: 0.9725\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.0524 - acc: 0.9803\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0846 - acc: 0.9685\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1355 - acc: 0.9431\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1440 - acc: 0.9435\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1464 - acc: 0.9359\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1427 - acc: 0.9409\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1479 - acc: 0.9372\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1257 - acc: 0.9480\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1197 - acc: 0.9493\n", "Epoch 8/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 40us/step - loss: 0.1098 - acc: 0.9568\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1152 - acc: 0.9520\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1094 - acc: 0.9544\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1151 - acc: 0.9552\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1049 - acc: 0.9551\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1228 - acc: 0.9493\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1332 - acc: 0.9441\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1177 - acc: 0.9486\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1035 - acc: 0.9566\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0915 - acc: 0.9615\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0909 - acc: 0.9630\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0987 - acc: 0.9582\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1146 - acc: 0.9527\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1087 - acc: 0.9549\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0793 - acc: 0.9713\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0758 - acc: 0.9678\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1036 - acc: 0.9588\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0954 - acc: 0.9612\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0714 - acc: 0.9711\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0677 - acc: 0.9728\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0830 - acc: 0.9647\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0840 - acc: 0.9669\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0828 - acc: 0.9667\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0890 - acc: 0.9644\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0768 - acc: 0.9693\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0529 - acc: 0.9799\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0781 - acc: 0.9684\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0730 - acc: 0.9717\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0599 - acc: 0.9754\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0793 - acc: 0.9691\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1251 - acc: 0.9524\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0673 - acc: 0.9725\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0511 - acc: 0.9813\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0556 - acc: 0.9765\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0460 - acc: 0.9817\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0696 - acc: 0.9729\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0513 - acc: 0.9803\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0740 - acc: 0.9714\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0954 - acc: 0.9616\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0441 - acc: 0.9834\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0483 - acc: 0.9808\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0664 - acc: 0.9740\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0597 - acc: 0.9761\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1939 - acc: 0.9188\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1837 - acc: 0.9237\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1779 - acc: 0.9273\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1792 - acc: 0.9254\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1800 - acc: 0.9276\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1622 - acc: 0.9320\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1568 - acc: 0.9365\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.2059 - acc: 0.9133\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1762 - acc: 0.9289\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1577 - acc: 0.9344\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1512 - acc: 0.9373\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1565 - acc: 0.9351\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1503 - acc: 0.9388\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1459 - acc: 0.9386\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1393 - acc: 0.9431\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1636 - acc: 0.9291\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1374 - acc: 0.9450\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1406 - acc: 0.9420\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1454 - acc: 0.9416\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1407 - acc: 0.9441\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1197 - acc: 0.9524\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1392 - acc: 0.9423\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1309 - acc: 0.9465\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1206 - acc: 0.9508\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1095 - acc: 0.9579\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1245 - acc: 0.9497\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1181 - acc: 0.9522\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1065 - acc: 0.9573\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1206 - acc: 0.9501\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1159 - acc: 0.9530\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1066 - acc: 0.9570\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1061 - acc: 0.9586\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1080 - acc: 0.9559\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1019 - acc: 0.9592\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0918 - acc: 0.9625\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0914 - acc: 0.9626\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1029 - acc: 0.9575\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1058 - acc: 0.9578\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0942 - acc: 0.9630\n", "Epoch 40/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 41us/step - loss: 0.0963 - acc: 0.9616\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0933 - acc: 0.9629\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1359 - acc: 0.9475\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1004 - acc: 0.9590\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0743 - acc: 0.9721\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0777 - acc: 0.9678\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0869 - acc: 0.9659\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1074 - acc: 0.9560\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0902 - acc: 0.9647\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0876 - acc: 0.9645\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1024 - acc: 0.9556\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1516 - acc: 0.9380\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1453 - acc: 0.9384\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1270 - acc: 0.9493\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1569 - acc: 0.9369\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1373 - acc: 0.9421\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1293 - acc: 0.9471\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1377 - acc: 0.9427\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1346 - acc: 0.9469\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1294 - acc: 0.9456\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1249 - acc: 0.9489\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1288 - acc: 0.9465\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1481 - acc: 0.9375\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1034 - acc: 0.9585\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1032 - acc: 0.9582\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1166 - acc: 0.9508\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1396 - acc: 0.9449\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1711 - acc: 0.9292\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0846 - acc: 0.9674\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0822 - acc: 0.9647\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0766 - acc: 0.9695\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0801 - acc: 0.9678\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0875 - acc: 0.9669\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0923 - acc: 0.9630\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0722 - acc: 0.9709\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1165 - acc: 0.9545\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0970 - acc: 0.9621\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0830 - acc: 0.9667\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0976 - acc: 0.9630\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0989 - acc: 0.9616\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0804 - acc: 0.9669\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0838 - acc: 0.9638\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0687 - acc: 0.9735\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0892 - acc: 0.9630\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0756 - acc: 0.9706\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0760 - acc: 0.9714\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1040 - acc: 0.9597\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0676 - acc: 0.9721\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0759 - acc: 0.9706\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0803 - acc: 0.9678\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0692 - acc: 0.9721\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0966 - acc: 0.9600\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0586 - acc: 0.9773\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0610 - acc: 0.9750\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0484 - acc: 0.9816\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0562 - acc: 0.9787\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0575 - acc: 0.9748\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0624 - acc: 0.9754\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0761 - acc: 0.9676\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0553 - acc: 0.9794\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0568 - acc: 0.9794\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1792 - acc: 0.9248\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1620 - acc: 0.9336\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1525 - acc: 0.9366\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1652 - acc: 0.9315\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1501 - acc: 0.9383\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1410 - acc: 0.9409\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1448 - acc: 0.9405\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1481 - acc: 0.9390\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1489 - acc: 0.9402\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1283 - acc: 0.9471\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1339 - acc: 0.9464\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1301 - acc: 0.9461\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1289 - acc: 0.9464\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1258 - acc: 0.9472\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1023 - acc: 0.9584\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1303 - acc: 0.9464\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1156 - acc: 0.9490\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1125 - acc: 0.9542\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1306 - acc: 0.9456\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1096 - acc: 0.9540\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1003 - acc: 0.9593\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1258 - acc: 0.9479\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 23/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0921 - acc: 0.9611\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0953 - acc: 0.9599\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1071 - acc: 0.9544\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1078 - acc: 0.9546\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1070 - acc: 0.9575\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0913 - acc: 0.9643\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0848 - acc: 0.9659\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0844 - acc: 0.9654\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0962 - acc: 0.9604\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0799 - acc: 0.9687\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1108 - acc: 0.9557\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0983 - acc: 0.9564\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0942 - acc: 0.9618\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0826 - acc: 0.9682\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0878 - acc: 0.9608\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0941 - acc: 0.9616\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0957 - acc: 0.9608\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0903 - acc: 0.9612\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0798 - acc: 0.9667\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0760 - acc: 0.9692\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0634 - acc: 0.9747\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0774 - acc: 0.9684\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0688 - acc: 0.9726\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0811 - acc: 0.9673\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0548 - acc: 0.9788\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0538 - acc: 0.9788\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0724 - acc: 0.9696\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0627 - acc: 0.9750\n", " 0.9185354018086905\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1904 - acc: 0.9236\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1699 - acc: 0.9321\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1787 - acc: 0.9281\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1766 - acc: 0.9302\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1816 - acc: 0.9248\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1759 - acc: 0.9258\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1383 - acc: 0.9471\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1542 - acc: 0.9358\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1571 - acc: 0.9364\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1444 - acc: 0.9406\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1418 - acc: 0.9434\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1367 - acc: 0.9457\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1437 - acc: 0.9410\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1321 - acc: 0.9467\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1228 - acc: 0.9537\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1274 - acc: 0.9494\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1219 - acc: 0.9497\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1239 - acc: 0.9505\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1271 - acc: 0.9509\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1482 - acc: 0.9384\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1310 - acc: 0.9493\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1060 - acc: 0.9567\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1015 - acc: 0.9615\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0969 - acc: 0.9641\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1156 - acc: 0.9540\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1050 - acc: 0.9601\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1250 - acc: 0.9513\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1041 - acc: 0.9577\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1170 - acc: 0.9540\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1258 - acc: 0.9509\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0972 - acc: 0.9611\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0947 - acc: 0.9625\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1068 - acc: 0.9578\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1003 - acc: 0.9607\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0903 - acc: 0.9636\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0812 - acc: 0.9698\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0844 - acc: 0.9678\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0960 - acc: 0.9605\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1011 - acc: 0.9579\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0919 - acc: 0.9629\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0708 - acc: 0.9724\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0790 - acc: 0.9663\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0687 - acc: 0.9729\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0999 - acc: 0.9599\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0920 - acc: 0.9645\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0691 - acc: 0.9758\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0679 - acc: 0.9747\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0728 - acc: 0.9702\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0682 - acc: 0.9747\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0688 - acc: 0.9736\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1554 - acc: 0.9376\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1638 - acc: 0.9317\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1481 - acc: 0.9376\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1625 - acc: 0.9361\n", "Epoch 5/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 40us/step - loss: 0.1356 - acc: 0.9478\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1222 - acc: 0.9494\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1428 - acc: 0.9408\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1343 - acc: 0.9447\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.1266 - acc: 0.9507\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1182 - acc: 0.9522\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1274 - acc: 0.9491\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1128 - acc: 0.9560\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1443 - acc: 0.9427\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1047 - acc: 0.9585\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1090 - acc: 0.9551\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1067 - acc: 0.9559\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1079 - acc: 0.9571\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1036 - acc: 0.9604\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1033 - acc: 0.9588\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1210 - acc: 0.9529\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0999 - acc: 0.9610\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.1031 - acc: 0.9581\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1113 - acc: 0.9549\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0929 - acc: 0.9619\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0800 - acc: 0.9681\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0999 - acc: 0.9615\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0945 - acc: 0.9625\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0988 - acc: 0.9618\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0857 - acc: 0.9655\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0715 - acc: 0.9715\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.0808 - acc: 0.9684\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0821 - acc: 0.9654\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0715 - acc: 0.9739\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0857 - acc: 0.9636\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0629 - acc: 0.9746\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0868 - acc: 0.9667\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0876 - acc: 0.9681\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0883 - acc: 0.9655\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0659 - acc: 0.9743\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0635 - acc: 0.9739\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0706 - acc: 0.9731\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0746 - acc: 0.9693\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0633 - acc: 0.9724\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0638 - acc: 0.9755\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0476 - acc: 0.9806\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0557 - acc: 0.9764\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0596 - acc: 0.9762\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0841 - acc: 0.9678\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0780 - acc: 0.9677\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0657 - acc: 0.9743\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1598 - acc: 0.9369\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.1519 - acc: 0.9392\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1344 - acc: 0.9475\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1308 - acc: 0.9478\n", "Epoch 5/50\n", "7275/7275 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[==============================] - 0s 41us/step - loss: 0.0868 - acc: 0.9674\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0883 - acc: 0.9638\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0791 - acc: 0.9692\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0872 - acc: 0.9630\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0746 - acc: 0.9703\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0928 - acc: 0.9629\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0869 - acc: 0.9662\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0686 - acc: 0.9740\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1199 - acc: 0.9549\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0761 - acc: 0.9703\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0723 - acc: 0.9713\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0702 - acc: 0.9718\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0819 - acc: 0.9666\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0794 - acc: 0.9685\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0677 - acc: 0.9728\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 38/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0815 - acc: 0.9696\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0743 - acc: 0.9715\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0706 - acc: 0.9739\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0863 - acc: 0.9662\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0557 - acc: 0.9772\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0508 - acc: 0.9814\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0514 - acc: 0.9808\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0446 - acc: 0.9841\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0714 - acc: 0.9737\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0962 - acc: 0.9640\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0541 - acc: 0.9788\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0582 - acc: 0.9768\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0679 - acc: 0.9733\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.1581 - acc: 0.9362\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.1554 - acc: 0.9384\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1629 - acc: 0.9333\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1539 - acc: 0.9369\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1473 - acc: 0.9408\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1440 - acc: 0.9414\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1441 - acc: 0.9414\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1340 - acc: 0.9446\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1174 - acc: 0.9516\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1266 - acc: 0.9479\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1372 - acc: 0.9438\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1216 - acc: 0.9519\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1272 - acc: 0.9469\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 61us/step - loss: 0.1177 - acc: 0.9509\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.1294 - acc: 0.9443\n", "Epoch 16/50\n", "7275/7275 [==============================] - 1s 83us/step - loss: 0.1431 - acc: 0.9416\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 55us/step - loss: 0.1350 - acc: 0.9480\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.1119 - acc: 0.9552\n", "Epoch 19/50\n", "7275/7275 [==============================] - 1s 86us/step - loss: 0.0986 - acc: 0.9619\n", "Epoch 20/50\n", "7275/7275 [==============================] - 1s 95us/step - loss: 0.0957 - acc: 0.9592\n", "Epoch 21/50\n", "7275/7275 [==============================] - 1s 73us/step - loss: 0.0965 - acc: 0.9597\n", "Epoch 22/50\n", "7275/7275 [==============================] - 1s 84us/step - loss: 0.1131 - acc: 0.9537\n", "Epoch 23/50\n", "7275/7275 [==============================] - 1s 90us/step - loss: 0.0955 - acc: 0.9619\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 64us/step - loss: 0.1130 - acc: 0.9562\n", "Epoch 25/50\n", "7275/7275 [==============================] - 1s 69us/step - loss: 0.0955 - acc: 0.9625\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.1224 - acc: 0.9489\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0903 - acc: 0.9636\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0942 - acc: 0.9616\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1094 - acc: 0.9555\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0778 - acc: 0.9688\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.0823 - acc: 0.9660\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0738 - acc: 0.9704\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.0798 - acc: 0.9673\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 61us/step - loss: 0.0609 - acc: 0.9748\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0944 - acc: 0.9612\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0908 - acc: 0.9649\n", "Epoch 37/50\n", "7275/7275 [==============================] - 1s 80us/step - loss: 0.1160 - acc: 0.9524\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0801 - acc: 0.9685\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 59us/step - loss: 0.0739 - acc: 0.9703\n", "Epoch 40/50\n", "7275/7275 [==============================] - 1s 74us/step - loss: 0.0757 - acc: 0.9703\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0561 - acc: 0.9792\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0704 - acc: 0.9718\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.0678 - acc: 0.9728\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0548 - acc: 0.9791\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 63us/step - loss: 0.0779 - acc: 0.9688\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0874 - acc: 0.9644\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0631 - acc: 0.9747\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.0792 - acc: 0.9681\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.0837 - acc: 0.9696\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0434 - acc: 0.9839\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1502 - acc: 0.9375\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1331 - acc: 0.9467\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1560 - acc: 0.9331\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1370 - acc: 0.9409\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1239 - acc: 0.9449\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1228 - acc: 0.9476\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.1523 - acc: 0.9380\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1190 - acc: 0.9513\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1194 - acc: 0.9493\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.1263 - acc: 0.9500\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1266 - acc: 0.9468\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1157 - acc: 0.9538\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 47us/step - loss: 0.1060 - acc: 0.9581\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1335 - acc: 0.9430\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.0989 - acc: 0.9603\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0941 - acc: 0.9621\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.0981 - acc: 0.9600\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.1226 - acc: 0.9490\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.1117 - acc: 0.9518\n", "Epoch 20/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 42us/step - loss: 0.0974 - acc: 0.9621\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.1080 - acc: 0.9570\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0852 - acc: 0.9658\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0844 - acc: 0.9681\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0737 - acc: 0.9709\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0910 - acc: 0.9623\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0762 - acc: 0.9677\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0812 - acc: 0.9665\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0657 - acc: 0.9739\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0684 - acc: 0.9736\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0790 - acc: 0.9700\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0934 - acc: 0.9605\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0964 - acc: 0.9627\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0870 - acc: 0.9660\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.0587 - acc: 0.9770\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0565 - acc: 0.9776\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0624 - acc: 0.9766\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0594 - acc: 0.9766\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0601 - acc: 0.9755\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0757 - acc: 0.9678\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0984 - acc: 0.9621\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.0849 - acc: 0.9659\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.0784 - acc: 0.9692\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0476 - acc: 0.9813\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0595 - acc: 0.9755\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0511 - acc: 0.9787\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0565 - acc: 0.9780\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0701 - acc: 0.9725\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0478 - acc: 0.9823\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.0411 - acc: 0.9836\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.0568 - acc: 0.9780\n", " 0.9223157610959977\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "array([4.02989972e-04, 2.61568720e-03, 1.86282367e-01, ...,\n", " 7.70919919e-01, 1.60739850e-03, 4.49502768e-05])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv = StratifiedKFold(n_splits=10)\n", "results = np.zeros_like(y, dtype=float)\n", "\n", "tprs = []\n", "aucs = []\n", "mean_fpr = np.linspace(0, 1, 100)\n", "\n", "i = 0\n", "for train, test in cv.split(X, y):\n", " keras.backend.clear_session()\n", " prbs=[]\n", " quant_trans = sklearn.preprocessing.QuantileTransformer(output_distribution='uniform').fit(X[train,:])\n", " for mod in range(5):\n", " print('>>')\n", " curr_try = 0\n", " while curr_try <10:\n", " print('.')\n", "\n", " model = Sequential()\n", " model.add(Dense(64, input_dim=X.shape[1], activation='relu'))\n", " model.add(Dense(64, activation='relu'))\n", " model.add(Dense(64, activation='relu'))\n", " model.add(Dense(64, activation='relu'))\n", " model.add(Dense(1, activation='sigmoid'))\n", " # Compile model\n", " opt = keras.optimizers.Adam(epsilon=None, amsgrad=True)\n", " model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])\n", " \n", " # Fit the model\n", " history = model.fit(quant_trans.transform(X[train,:]), y[train], epochs=50, batch_size=64, verbose=0)\n", " if history.history['acc'][-1] > 0.53:\n", " break\n", " else:\n", " curr_try += 1\n", "\n", " # Fit the model\n", " model.fit(quant_trans.transform(X[train,:]), y[train], epochs=50, batch_size=64, verbose=1)\n", " \n", " # evaluate the model\n", " probas_ = model.predict(quant_trans.transform(X[test,:]))\n", " prbs.append(probas_)\n", " # Average the predictions\n", " probas_ = np.mean(np.hstack(prbs), axis=1)\n", " results[test] = probas_\n", " \n", " # Compute ROC curve and area the curve\n", " fpr, tpr, thresholds = roc_curve(y[test], probas_[ :])\n", " print(' ' + str(auc(fpr, tpr)))\n", " tprs.append(interp(mean_fpr, fpr, tpr))\n", " tprs[-1][0] = 0.0\n", " roc_auc = auc(fpr, tpr)\n", " aucs.append(roc_auc)\n", " plt.plot(fpr, tpr, lw=1, alpha=0.3,\n", " label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n", "\n", " i += 1\n", "plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n", " label='Chance', alpha=.8)\n", "\n", "mean_tpr = np.mean(tprs, axis=0)\n", "mean_tpr[-1] = 1.0\n", "mean_auc = auc(mean_fpr, mean_tpr)\n", "std_auc = np.std(aucs)\n", "plt.plot(mean_fpr, mean_tpr, color='b',\n", " label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n", " lw=2, alpha=.8)\n", "\n", "std_tpr = np.std(tprs, axis=0)\n", "tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n", "tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n", "plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n", " label=r'$\\pm$ 1 std. dev.')\n", "\n", "plt.xlim([-0.05, 1.05])\n", "plt.ylim([-0.05, 1.05])\n", "plt.xlabel('False Positive Rate')\n", "plt.ylabel('True Positive Rate')\n", "plt.title('Receiver operating characteristic example')\n", "plt.legend(loc=\"lower right\")\n", "plt.show()\n", "results" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "df_results = pd.DataFrame(data={\"name\": names, 'pred': results})\n", "df_results.to_csv('/home/drewe/notebooks/genotox/pred.nn.v4.norm.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(results[y==0],100, color='red', alpha=0.5)\n", "plt.hist(results[y==1],100, color='blue', alpha=0.5)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "results[test] = probas_\n", "plt.plot(results)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4441 - acc: 0.7964\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4452 - acc: 0.7949\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4433 - acc: 0.7967\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4444 - acc: 0.7958\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4415 - acc: 0.7985\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4428 - acc: 0.8013\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4401 - acc: 0.7997\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4452 - acc: 0.7983\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4399 - acc: 0.8033\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4403 - acc: 0.8013\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4396 - acc: 0.8004\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4378 - acc: 0.8005\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4375 - acc: 0.8023\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4429 - acc: 0.7982\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4349 - acc: 0.8049\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4360 - acc: 0.8035\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4367 - acc: 0.8038\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4350 - acc: 0.8041\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4361 - acc: 0.8053\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4352 - acc: 0.8031\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4341 - acc: 0.8057\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4356 - acc: 0.8040\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4323 - acc: 0.8057\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4340 - acc: 0.8016\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4344 - acc: 0.8045\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4360 - acc: 0.8033\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4338 - acc: 0.8067\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4327 - acc: 0.8056\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4309 - acc: 0.8056\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4310 - acc: 0.8090\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4345 - acc: 0.8059\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4304 - acc: 0.8075\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4326 - acc: 0.8052\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4296 - acc: 0.8104\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4295 - acc: 0.8085\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4310 - acc: 0.8042\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4309 - acc: 0.8060\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4294 - acc: 0.8084\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4310 - acc: 0.8079\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4300 - acc: 0.8084\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8101\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4350 - acc: 0.8055\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4317 - acc: 0.8031\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4309 - acc: 0.8064\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4277 - acc: 0.8082\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4260 - acc: 0.8115\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8092\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4274 - acc: 0.8100\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4272 - acc: 0.8086\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4264 - acc: 0.8095\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4445 - acc: 0.8002\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4437 - acc: 0.7998\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4431 - acc: 0.8020\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4433 - acc: 0.7994\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4414 - acc: 0.8004\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4394 - acc: 0.8019\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4394 - acc: 0.8034\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4403 - acc: 0.7983\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4402 - acc: 0.7996\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4390 - acc: 0.7979\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4401 - acc: 0.7993\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4384 - acc: 0.8026\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4402 - acc: 0.7974\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4375 - acc: 0.8002\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4382 - acc: 0.8062\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4349 - acc: 0.8031\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4373 - acc: 0.8007\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4333 - acc: 0.8037\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4331 - acc: 0.8057\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4401 - acc: 0.8012\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4370 - acc: 0.8042\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4336 - acc: 0.8037\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4333 - acc: 0.8052\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4355 - acc: 0.8046\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4374 - acc: 0.8024\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4323 - acc: 0.8066\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4327 - acc: 0.8052\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4336 - acc: 0.8081\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 21us/step - loss: 0.4308 - acc: 0.8075\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4309 - acc: 0.8068\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4315 - acc: 0.8042\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4311 - acc: 0.8073\n", "Epoch 33/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 23us/step - loss: 0.4329 - acc: 0.8022\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4321 - acc: 0.8052\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4320 - acc: 0.8048\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4323 - acc: 0.8071\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4290 - acc: 0.8070\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4279 - acc: 0.8081\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 21us/step - loss: 0.4286 - acc: 0.8096\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4297 - acc: 0.8071\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4268 - acc: 0.8103\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4266 - acc: 0.8099\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4270 - acc: 0.8118\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4262 - acc: 0.8089\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4258 - acc: 0.8106\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4271 - acc: 0.8071\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4264 - acc: 0.8099\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4245 - acc: 0.8112\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4274 - acc: 0.8074\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4245 - acc: 0.8126\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4430 - acc: 0.7982\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4445 - acc: 0.7974\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4423 - acc: 0.7998\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4456 - acc: 0.7957\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4411 - acc: 0.7994\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4412 - acc: 0.8013\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4443 - acc: 0.7958\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4387 - acc: 0.8034\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4394 - acc: 0.8000\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4375 - acc: 0.8038\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.4382 - acc: 0.8011\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4387 - acc: 0.8019\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4389 - acc: 0.7989\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4389 - acc: 0.8009\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4419 - acc: 0.8020\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4372 - acc: 0.8033\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4354 - acc: 0.8044\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4341 - acc: 0.8063\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4392 - acc: 0.8018\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4397 - acc: 0.8018\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4355 - acc: 0.8042\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4355 - acc: 0.8022\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4343 - acc: 0.8082\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4373 - acc: 0.8042\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4337 - acc: 0.8063\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4320 - acc: 0.8027\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4315 - acc: 0.8070\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4324 - acc: 0.8056\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4336 - acc: 0.8066\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4293 - acc: 0.8068\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4313 - acc: 0.8063\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4295 - acc: 0.8081\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4305 - acc: 0.8053\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4295 - acc: 0.8053\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4286 - acc: 0.8090\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4311 - acc: 0.8055\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4295 - acc: 0.8070\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4304 - acc: 0.8073\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4288 - acc: 0.8074\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4329 - acc: 0.8066\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4302 - acc: 0.8018\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4296 - acc: 0.8093\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4307 - acc: 0.8068\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4326 - acc: 0.8048\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4267 - acc: 0.8085\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4286 - acc: 0.8049\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4274 - acc: 0.8103\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4278 - acc: 0.8100\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4254 - acc: 0.8110\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4262 - acc: 0.8090\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4415 - acc: 0.8002\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4442 - acc: 0.8027\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4436 - acc: 0.7983\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4405 - acc: 0.7997\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4402 - acc: 0.8008\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4411 - acc: 0.8013\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4417 - acc: 0.8023\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4391 - acc: 0.8015\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4401 - acc: 0.8018\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4388 - acc: 0.8012\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4399 - acc: 0.8002\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4390 - acc: 0.7993\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4384 - acc: 0.8035\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4360 - acc: 0.8008\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4368 - acc: 0.8027\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 16/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4379 - acc: 0.8048\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4343 - acc: 0.8046\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4359 - acc: 0.8034\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4350 - acc: 0.8055\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4351 - acc: 0.8024\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4401 - acc: 0.8004\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4355 - acc: 0.8026\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4342 - acc: 0.8064\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4352 - acc: 0.8055\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4334 - acc: 0.8046\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4311 - acc: 0.8081\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4326 - acc: 0.8037\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4302 - acc: 0.8100\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4306 - acc: 0.8074\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4316 - acc: 0.8048\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4314 - acc: 0.8078\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4323 - acc: 0.8099\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4322 - acc: 0.8059\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4300 - acc: 0.8078\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4293 - acc: 0.8077\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4336 - acc: 0.8040\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4314 - acc: 0.8046\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4290 - acc: 0.8070\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4328 - acc: 0.8071\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4303 - acc: 0.8068\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4284 - acc: 0.8089\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4287 - acc: 0.8106\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4276 - acc: 0.8089\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4302 - acc: 0.8088\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4264 - acc: 0.8101\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4262 - acc: 0.8090\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4282 - acc: 0.8114\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4264 - acc: 0.8097\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4257 - acc: 0.8085\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4259 - acc: 0.8107\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4422 - acc: 0.8001\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4409 - acc: 0.8016\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4432 - acc: 0.7963\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4401 - acc: 0.8033\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4400 - acc: 0.7986\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4406 - acc: 0.7993\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4413 - acc: 0.8012\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4400 - acc: 0.8013\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4412 - acc: 0.8033\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4412 - acc: 0.8004\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4391 - acc: 0.7990\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4396 - acc: 0.8029\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4407 - acc: 0.8037\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4391 - acc: 0.8005\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4363 - acc: 0.8008\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4370 - acc: 0.8056\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4354 - acc: 0.8044\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4332 - acc: 0.8051\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4342 - acc: 0.8079\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4351 - acc: 0.8020\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4352 - acc: 0.8011\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4358 - acc: 0.8029\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4351 - acc: 0.8040\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4341 - acc: 0.8048\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4339 - acc: 0.8026\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4341 - acc: 0.8030\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4315 - acc: 0.8055\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4322 - acc: 0.8079\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4306 - acc: 0.8068\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4324 - acc: 0.8062\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4329 - acc: 0.8059\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4330 - acc: 0.8051\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4324 - acc: 0.8057\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4351 - acc: 0.8008\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4296 - acc: 0.8066\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4289 - acc: 0.8108\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4320 - acc: 0.8029\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4300 - acc: 0.8048\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4281 - acc: 0.8085\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4269 - acc: 0.8079\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4288 - acc: 0.8075\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4279 - acc: 0.8101\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8055\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4287 - acc: 0.8044\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4268 - acc: 0.8056\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4253 - acc: 0.8099\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4248 - acc: 0.8114\n", "Epoch 48/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 24us/step - loss: 0.4285 - acc: 0.8090\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4272 - acc: 0.8075\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4257 - acc: 0.8103\n", " 0.8924720996467381\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4370 - acc: 0.8019\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4391 - acc: 0.7994\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4376 - acc: 0.8023\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4373 - acc: 0.8015\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4379 - acc: 0.8038\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4342 - acc: 0.8053\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4364 - acc: 0.8008\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4354 - acc: 0.7974\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4369 - acc: 0.7996\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4339 - acc: 0.8048\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4328 - acc: 0.8041\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4379 - acc: 0.7985\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4344 - acc: 0.8040\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4316 - acc: 0.8067\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4326 - acc: 0.8055\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4307 - acc: 0.8078\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4294 - acc: 0.8073\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4312 - acc: 0.8041\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4323 - acc: 0.8068\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4335 - acc: 0.8013\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4305 - acc: 0.8084\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4310 - acc: 0.8030\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4306 - acc: 0.8067\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4278 - acc: 0.8074\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4297 - acc: 0.8082\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4269 - acc: 0.8052\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4296 - acc: 0.8099\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8060\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8071\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4276 - acc: 0.8081\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4268 - acc: 0.8082\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4273 - acc: 0.8077\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4282 - acc: 0.8095\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4267 - acc: 0.8073\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4267 - acc: 0.8100\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4265 - acc: 0.8079\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4250 - acc: 0.8068\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4257 - acc: 0.8103\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4253 - acc: 0.8130\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4234 - acc: 0.8097\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4228 - acc: 0.8099\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4253 - acc: 0.8084\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4225 - acc: 0.8095\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4258 - acc: 0.8095\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4245 - acc: 0.8114\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4237 - acc: 0.8104\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4244 - acc: 0.8106\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4213 - acc: 0.8129\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4230 - acc: 0.8104\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4214 - acc: 0.8118\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4384 - acc: 0.7983\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4395 - acc: 0.8011\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4364 - acc: 0.8022\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4384 - acc: 0.8011\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4367 - acc: 0.8027\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4375 - acc: 0.8020\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4366 - acc: 0.8011\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4355 - acc: 0.8048\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4345 - acc: 0.8020\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4322 - acc: 0.8038\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4319 - acc: 0.8077\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4326 - acc: 0.8060\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4338 - acc: 0.8038\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4340 - acc: 0.8046\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4345 - acc: 0.8044\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4312 - acc: 0.8035\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4335 - acc: 0.8030\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4342 - acc: 0.8052\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4311 - acc: 0.8052\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4306 - acc: 0.8073\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4308 - acc: 0.8030\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4293 - acc: 0.8066\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4280 - acc: 0.8079\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4337 - acc: 0.8045\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4335 - acc: 0.8037\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4273 - acc: 0.8092\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4276 - acc: 0.8066\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4282 - acc: 0.8074\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4272 - acc: 0.8103\n", "Epoch 30/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 27us/step - loss: 0.4254 - acc: 0.8082\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4257 - acc: 0.8108\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4275 - acc: 0.8101\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4246 - acc: 0.8095\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4248 - acc: 0.8090\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4244 - acc: 0.8103\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4240 - acc: 0.8086\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4249 - acc: 0.8071\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4231 - acc: 0.8118\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4269 - acc: 0.8077\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4241 - acc: 0.8130\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4230 - acc: 0.8139\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4234 - acc: 0.8095\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4218 - acc: 0.8117\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4224 - acc: 0.8110\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4218 - acc: 0.8161\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4225 - acc: 0.8147\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4239 - acc: 0.8122\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4234 - acc: 0.8085\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4247 - acc: 0.8126\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4231 - acc: 0.8137\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4408 - acc: 0.7965\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4373 - acc: 0.8037\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4368 - acc: 0.8012\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4397 - acc: 0.8022\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4376 - acc: 0.7990\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4366 - acc: 0.8046\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4346 - acc: 0.8026\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4343 - acc: 0.8026\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4339 - acc: 0.8024\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4372 - acc: 0.8005\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4339 - acc: 0.8019\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4358 - acc: 0.8026\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4319 - acc: 0.8019\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4331 - acc: 0.8030\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4356 - acc: 0.8012\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4314 - acc: 0.8040\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4315 - acc: 0.8059\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4304 - acc: 0.8053\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8064\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4293 - acc: 0.8049\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4323 - acc: 0.8031\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4283 - acc: 0.8075\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4297 - acc: 0.8074\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4280 - acc: 0.8046\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4299 - acc: 0.8055\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4292 - acc: 0.8086\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4262 - acc: 0.8099\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4272 - acc: 0.8089\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4292 - acc: 0.8048\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4250 - acc: 0.8117\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4298 - acc: 0.8090\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4271 - acc: 0.8070\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4283 - acc: 0.8082\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4280 - acc: 0.8082\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4226 - acc: 0.8133\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4265 - acc: 0.8095\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8079\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4231 - acc: 0.8126\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4247 - acc: 0.8107\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4254 - acc: 0.8059\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4242 - acc: 0.8085\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4275 - acc: 0.8062\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4219 - acc: 0.8130\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4282 - acc: 0.8055\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4216 - acc: 0.8122\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4224 - acc: 0.8130\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4248 - acc: 0.8075\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4226 - acc: 0.8106\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4209 - acc: 0.8145\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4209 - acc: 0.8108\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4390 - acc: 0.8005\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4407 - acc: 0.7986\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4377 - acc: 0.8020\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4389 - acc: 0.7998\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4366 - acc: 0.8013\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4366 - acc: 0.8031\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4373 - acc: 0.8020\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4346 - acc: 0.8023\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4332 - acc: 0.8066\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4388 - acc: 0.8007\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4343 - acc: 0.8019\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4354 - acc: 0.8023\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 13/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4328 - acc: 0.8051\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4337 - acc: 0.8051\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4326 - acc: 0.8033\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4309 - acc: 0.8042\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4316 - acc: 0.8045\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4320 - acc: 0.8064\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4349 - acc: 0.8020\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4303 - acc: 0.8078\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4303 - acc: 0.8079\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4318 - acc: 0.8034\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4309 - acc: 0.8034\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4310 - acc: 0.8062\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8056\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4291 - acc: 0.8020\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4313 - acc: 0.8055\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4294 - acc: 0.8055\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4280 - acc: 0.8071\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4304 - acc: 0.8097\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4257 - acc: 0.8093\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4271 - acc: 0.8107\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4250 - acc: 0.8130\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4259 - acc: 0.8110\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4285 - acc: 0.8042\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4258 - acc: 0.8095\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4273 - acc: 0.8068\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4241 - acc: 0.8097\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4248 - acc: 0.8115\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4283 - acc: 0.8042\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4230 - acc: 0.8103\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4230 - acc: 0.8106\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.4294 - acc: 0.8057\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.4250 - acc: 0.8078\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.4220 - acc: 0.8123\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4233 - acc: 0.8100\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4236 - acc: 0.8115\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4209 - acc: 0.8130\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 63us/step - loss: 0.4214 - acc: 0.8148\n", "Epoch 50/50\n", "7274/7274 [==============================] - 1s 69us/step - loss: 0.4223 - acc: 0.8128\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4409 - acc: 0.7968\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4386 - acc: 0.7986\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4399 - acc: 0.7997\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4377 - acc: 0.8041\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4355 - acc: 0.8051\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4363 - acc: 0.7998\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4361 - acc: 0.8020\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4346 - acc: 0.8031\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4337 - acc: 0.8029\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4360 - acc: 0.8020\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4334 - acc: 0.8029\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4340 - acc: 0.8057\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 66us/step - loss: 0.4321 - acc: 0.8033\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.4331 - acc: 0.8052\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4339 - acc: 0.8053\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 60us/step - loss: 0.4362 - acc: 0.8037\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.4327 - acc: 0.8029\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4346 - acc: 0.8040\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4295 - acc: 0.8052\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 50us/step - loss: 0.4298 - acc: 0.8067\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4300 - acc: 0.8059\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4293 - acc: 0.8073\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4305 - acc: 0.8089\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4305 - acc: 0.8066\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4281 - acc: 0.8053\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4278 - acc: 0.8066\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.4270 - acc: 0.8070\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4284 - acc: 0.8073\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4265 - acc: 0.8079\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4281 - acc: 0.8089\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4292 - acc: 0.8078\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4258 - acc: 0.8088\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4277 - acc: 0.8090\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4259 - acc: 0.8074\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.4268 - acc: 0.8079\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 52us/step - loss: 0.4254 - acc: 0.8078\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 46us/step - loss: 0.4230 - acc: 0.8108\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4238 - acc: 0.8095\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4257 - acc: 0.8078\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4259 - acc: 0.8067\n", "Epoch 41/50\n", "7274/7274 [==============================] - 1s 70us/step - loss: 0.4240 - acc: 0.8114\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 53us/step - loss: 0.4229 - acc: 0.8104\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4277 - acc: 0.8067\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.4248 - acc: 0.8082\n", "Epoch 45/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 34us/step - loss: 0.4226 - acc: 0.8110\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4234 - acc: 0.8099\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.4217 - acc: 0.8110\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 59us/step - loss: 0.4243 - acc: 0.8112\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 57us/step - loss: 0.4221 - acc: 0.8099\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4226 - acc: 0.8136\n", " 0.8678018310943784\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4351 - acc: 0.8044\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4358 - acc: 0.8023\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4412 - acc: 0.8000\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.4316 - acc: 0.8044\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4341 - acc: 0.8011\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4349 - acc: 0.8035\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4351 - acc: 0.8027\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4349 - acc: 0.8020\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4296 - acc: 0.8071\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4329 - acc: 0.8057\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4409 - acc: 0.7996\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4290 - acc: 0.8074\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4315 - acc: 0.8081\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4288 - acc: 0.8063\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4323 - acc: 0.8027\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4316 - acc: 0.8038\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4272 - acc: 0.8095\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4274 - acc: 0.8075\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4275 - acc: 0.8081\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4282 - acc: 0.8070\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4273 - acc: 0.8055\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4253 - acc: 0.8104\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4265 - acc: 0.8096\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4253 - acc: 0.8099\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4246 - acc: 0.8112\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4246 - acc: 0.8107\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4251 - acc: 0.8089\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4246 - acc: 0.8118\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4283 - acc: 0.8070\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4245 - acc: 0.8129\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4249 - acc: 0.8082\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4252 - acc: 0.8107\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4248 - acc: 0.8111\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4225 - acc: 0.8132\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4250 - acc: 0.8075\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4243 - acc: 0.8084\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4202 - acc: 0.8114\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4220 - acc: 0.8122\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4204 - acc: 0.8121\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4246 - acc: 0.8093\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4205 - acc: 0.8129\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4226 - acc: 0.8111\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4197 - acc: 0.8118\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4189 - acc: 0.8136\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4236 - acc: 0.8132\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4199 - acc: 0.8162\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4189 - acc: 0.8126\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4191 - acc: 0.8150\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4166 - acc: 0.8158\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4176 - acc: 0.8162\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4347 - acc: 0.8046\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4356 - acc: 0.8034\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4351 - acc: 0.8044\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4330 - acc: 0.8073\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4376 - acc: 0.8019\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4340 - acc: 0.8068\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4316 - acc: 0.8042\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4323 - acc: 0.8030\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4353 - acc: 0.8023\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4304 - acc: 0.8053\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4351 - acc: 0.8048\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4311 - acc: 0.8084\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4317 - acc: 0.8056\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4298 - acc: 0.8089\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4289 - acc: 0.8057\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4330 - acc: 0.8044\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 42us/step - loss: 0.4301 - acc: 0.8045\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4288 - acc: 0.8096\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4278 - acc: 0.8090\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.4284 - acc: 0.8089\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4304 - acc: 0.8092\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4273 - acc: 0.8096\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4273 - acc: 0.8063\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4299 - acc: 0.8049\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4290 - acc: 0.8062\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4271 - acc: 0.8046\n", "Epoch 27/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 34us/step - loss: 0.4258 - acc: 0.8077\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 41us/step - loss: 0.4261 - acc: 0.8082\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4242 - acc: 0.8114\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4256 - acc: 0.8101\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4250 - acc: 0.8117\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4232 - acc: 0.8092\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 40us/step - loss: 0.4227 - acc: 0.8107\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 47us/step - loss: 0.4237 - acc: 0.8121\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4241 - acc: 0.8101\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4244 - acc: 0.8100\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4236 - acc: 0.8126\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4225 - acc: 0.8111\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4227 - acc: 0.8112\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4215 - acc: 0.8152\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4206 - acc: 0.8147\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4207 - acc: 0.8143\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4272 - acc: 0.8110\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4220 - acc: 0.8122\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4190 - acc: 0.8151\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4211 - acc: 0.8119\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4209 - acc: 0.8090\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4186 - acc: 0.8159\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4197 - acc: 0.8121\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4192 - acc: 0.8143\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4378 - acc: 0.8029\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4359 - acc: 0.8031\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4346 - acc: 0.8041\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4355 - acc: 0.8009\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4353 - acc: 0.8022\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4372 - acc: 0.8034\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4321 - acc: 0.8016\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4355 - acc: 0.8026\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4318 - acc: 0.8023\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4328 - acc: 0.8035\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4335 - acc: 0.8030\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8077\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4315 - acc: 0.8052\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4313 - acc: 0.8088\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4326 - acc: 0.8001\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4288 - acc: 0.8062\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4303 - acc: 0.8055\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4316 - acc: 0.8013\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 43us/step - loss: 0.4273 - acc: 0.8074\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4280 - acc: 0.8042\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8103\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4259 - acc: 0.8086\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8073\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4304 - acc: 0.8060\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4285 - acc: 0.8066\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4276 - acc: 0.8090\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4250 - acc: 0.8081\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4259 - acc: 0.8097\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4257 - acc: 0.8121\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4260 - acc: 0.8092\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4267 - acc: 0.8096\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4263 - acc: 0.8079\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4229 - acc: 0.8108\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4249 - acc: 0.8108\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4247 - acc: 0.8079\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4208 - acc: 0.8126\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4270 - acc: 0.8057\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4214 - acc: 0.8133\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4234 - acc: 0.8106\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4218 - acc: 0.8129\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4210 - acc: 0.8143\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4205 - acc: 0.8140\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4207 - acc: 0.8136\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4187 - acc: 0.8154\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4211 - acc: 0.8141\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4218 - acc: 0.8103\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4183 - acc: 0.8141\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4196 - acc: 0.8111\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4229 - acc: 0.8101\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4189 - acc: 0.8156\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4364 - acc: 0.7986\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4389 - acc: 0.8013\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4343 - acc: 0.8052\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4328 - acc: 0.8062\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4339 - acc: 0.8027\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4341 - acc: 0.8053\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4341 - acc: 0.8018\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4337 - acc: 0.8035\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4317 - acc: 0.8045\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 10/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4325 - acc: 0.8081\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4293 - acc: 0.8038\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4299 - acc: 0.8078\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4283 - acc: 0.8078\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4297 - acc: 0.8057\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4312 - acc: 0.8060\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4290 - acc: 0.8078\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4290 - acc: 0.8115\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4278 - acc: 0.8081\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4278 - acc: 0.8092\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4291 - acc: 0.8068\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4286 - acc: 0.8048\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4270 - acc: 0.8067\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4264 - acc: 0.8059\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4254 - acc: 0.8084\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4259 - acc: 0.8078\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4266 - acc: 0.8095\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4245 - acc: 0.8081\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 54us/step - loss: 0.4281 - acc: 0.8073\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4276 - acc: 0.8068\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8070\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4260 - acc: 0.8095\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4239 - acc: 0.8108\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4274 - acc: 0.8100\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4258 - acc: 0.8106\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4227 - acc: 0.8141\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4236 - acc: 0.8104\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4212 - acc: 0.8137\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4251 - acc: 0.8078\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4212 - acc: 0.8107\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4194 - acc: 0.8145\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4208 - acc: 0.8096\n", "Epoch 42/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4191 - acc: 0.8117\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 25us/step - loss: 0.4217 - acc: 0.8130\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4212 - acc: 0.8139\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 23us/step - loss: 0.4182 - acc: 0.8108\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 22us/step - loss: 0.4213 - acc: 0.8122\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4182 - acc: 0.8140\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4189 - acc: 0.8137\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4182 - acc: 0.8097\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 24us/step - loss: 0.4228 - acc: 0.8126\n", ">>\n", ".\n", "Epoch 1/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4364 - acc: 0.8019\n", "Epoch 2/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4378 - acc: 0.8013\n", "Epoch 3/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4380 - acc: 0.7990\n", "Epoch 4/50\n", "7274/7274 [==============================] - 0s 29us/step - loss: 0.4373 - acc: 0.8035\n", "Epoch 5/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4372 - acc: 0.8044\n", "Epoch 6/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4330 - acc: 0.8059\n", "Epoch 7/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4339 - acc: 0.8024\n", "Epoch 8/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4365 - acc: 0.8011\n", "Epoch 9/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4342 - acc: 0.8055\n", "Epoch 10/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4318 - acc: 0.8042\n", "Epoch 11/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4307 - acc: 0.8066\n", "Epoch 12/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4332 - acc: 0.8045\n", "Epoch 13/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4321 - acc: 0.8049\n", "Epoch 14/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4280 - acc: 0.8053\n", "Epoch 15/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4300 - acc: 0.8064\n", "Epoch 16/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4362 - acc: 0.8037\n", "Epoch 17/50\n", "7274/7274 [==============================] - 0s 35us/step - loss: 0.4313 - acc: 0.8037\n", "Epoch 18/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4280 - acc: 0.8103\n", "Epoch 19/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4321 - acc: 0.8019\n", "Epoch 20/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4275 - acc: 0.8077\n", "Epoch 21/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4295 - acc: 0.8086\n", "Epoch 22/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4277 - acc: 0.8060\n", "Epoch 23/50\n", "7274/7274 [==============================] - 0s 38us/step - loss: 0.4323 - acc: 0.8062\n", "Epoch 24/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4256 - acc: 0.8095\n", "Epoch 25/50\n", "7274/7274 [==============================] - 0s 30us/step - loss: 0.4271 - acc: 0.8062\n", "Epoch 26/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4283 - acc: 0.8075\n", "Epoch 27/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4265 - acc: 0.8090\n", "Epoch 28/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4235 - acc: 0.8107\n", "Epoch 29/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4252 - acc: 0.8096\n", "Epoch 30/50\n", "7274/7274 [==============================] - 0s 37us/step - loss: 0.4247 - acc: 0.8110\n", "Epoch 31/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4273 - acc: 0.8089\n", "Epoch 32/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4235 - acc: 0.8084\n", "Epoch 33/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4219 - acc: 0.8104\n", "Epoch 34/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4234 - acc: 0.8110\n", "Epoch 35/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4252 - acc: 0.8095\n", "Epoch 36/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4262 - acc: 0.8077\n", "Epoch 37/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4213 - acc: 0.8128\n", "Epoch 38/50\n", "7274/7274 [==============================] - 0s 39us/step - loss: 0.4232 - acc: 0.8106\n", "Epoch 39/50\n", "7274/7274 [==============================] - 0s 36us/step - loss: 0.4209 - acc: 0.8154\n", "Epoch 40/50\n", "7274/7274 [==============================] - 0s 32us/step - loss: 0.4244 - acc: 0.8107\n", "Epoch 41/50\n", "7274/7274 [==============================] - 0s 31us/step - loss: 0.4200 - acc: 0.8128\n", "Epoch 42/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7274/7274 [==============================] - 0s 31us/step - loss: 0.4212 - acc: 0.8154\n", "Epoch 43/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4228 - acc: 0.8118\n", "Epoch 44/50\n", "7274/7274 [==============================] - 0s 34us/step - loss: 0.4191 - acc: 0.8123\n", "Epoch 45/50\n", "7274/7274 [==============================] - 0s 33us/step - loss: 0.4248 - acc: 0.8086\n", "Epoch 46/50\n", "7274/7274 [==============================] - 0s 28us/step - loss: 0.4209 - acc: 0.8143\n", "Epoch 47/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4202 - acc: 0.8141\n", "Epoch 48/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4177 - acc: 0.8150\n", "Epoch 49/50\n", "7274/7274 [==============================] - 0s 27us/step - loss: 0.4187 - acc: 0.8150\n", "Epoch 50/50\n", "7274/7274 [==============================] - 0s 26us/step - loss: 0.4177 - acc: 0.8136\n", " 0.8509821657763817\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4348 - acc: 0.8044\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4344 - acc: 0.8047\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4349 - acc: 0.8040\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4352 - acc: 0.8021\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4334 - acc: 0.8055\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4352 - acc: 0.8026\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4357 - acc: 0.8036\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4365 - acc: 0.8033\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4338 - acc: 0.8092\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4315 - acc: 0.8038\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4321 - acc: 0.8058\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4319 - acc: 0.8058\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4310 - acc: 0.8074\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4313 - acc: 0.8065\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4303 - acc: 0.8074\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4314 - acc: 0.8054\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4309 - acc: 0.8056\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4295 - acc: 0.8040\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4284 - acc: 0.8078\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4347 - acc: 0.8023\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4291 - acc: 0.8080\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4305 - acc: 0.8047\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.4268 - acc: 0.8092\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4263 - acc: 0.8081\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4258 - acc: 0.8113\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4272 - acc: 0.8073\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4271 - acc: 0.8085\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4294 - acc: 0.8062\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4256 - acc: 0.8102\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4248 - acc: 0.8109\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4262 - acc: 0.8084\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4260 - acc: 0.8118\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4231 - acc: 0.8132\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4224 - acc: 0.8121\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4228 - acc: 0.8095\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4245 - acc: 0.8098\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4257 - acc: 0.8111\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4223 - acc: 0.8107\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4224 - acc: 0.8128\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4224 - acc: 0.8109\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4248 - acc: 0.8139\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4230 - acc: 0.8102\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4212 - acc: 0.8124\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4218 - acc: 0.8142\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4203 - acc: 0.8107\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4199 - acc: 0.8159\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4206 - acc: 0.8143\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4199 - acc: 0.8125\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4187 - acc: 0.8146\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4215 - acc: 0.8132\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4360 - acc: 0.8029\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.7993\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4365 - acc: 0.8049\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4390 - acc: 0.7996\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4382 - acc: 0.8021\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4342 - acc: 0.8060\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4335 - acc: 0.8040\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4374 - acc: 0.8026\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4373 - acc: 0.8047\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4346 - acc: 0.8014\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4321 - acc: 0.8069\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4310 - acc: 0.8076\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4345 - acc: 0.8040\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4340 - acc: 0.8029\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4309 - acc: 0.8040\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4304 - acc: 0.8060\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4318 - acc: 0.8069\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4330 - acc: 0.8048\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4292 - acc: 0.8066\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8060\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4297 - acc: 0.8080\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8070\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4271 - acc: 0.8087\n", "Epoch 24/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 25us/step - loss: 0.4275 - acc: 0.8084\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4273 - acc: 0.8073\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4278 - acc: 0.8069\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8069\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4259 - acc: 0.8095\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4269 - acc: 0.8107\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4254 - acc: 0.8088\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4256 - acc: 0.8073\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4267 - acc: 0.8089\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4256 - acc: 0.8092\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4270 - acc: 0.8088\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4231 - acc: 0.8074\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4226 - acc: 0.8122\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4229 - acc: 0.8103\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4210 - acc: 0.8135\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4254 - acc: 0.8091\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4241 - acc: 0.8087\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4245 - acc: 0.8106\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4237 - acc: 0.8114\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4216 - acc: 0.8135\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4213 - acc: 0.8100\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4208 - acc: 0.8142\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4197 - acc: 0.8144\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4207 - acc: 0.8142\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4192 - acc: 0.8128\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4223 - acc: 0.8092\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4187 - acc: 0.8135\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4367 - acc: 0.8032\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4397 - acc: 0.7989\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4402 - acc: 0.8032\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4353 - acc: 0.8007\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4343 - acc: 0.8018\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4339 - acc: 0.8054\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.7999\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4358 - acc: 0.8011\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4326 - acc: 0.8023\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4338 - acc: 0.8037\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4322 - acc: 0.8034\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4337 - acc: 0.8041\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4324 - acc: 0.8041\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4316 - acc: 0.8036\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4310 - acc: 0.8069\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4311 - acc: 0.8027\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4311 - acc: 0.8044\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4312 - acc: 0.8060\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4309 - acc: 0.8082\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4306 - acc: 0.8088\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4299 - acc: 0.8103\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4298 - acc: 0.8048\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8076\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4314 - acc: 0.8059\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4266 - acc: 0.8106\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4271 - acc: 0.8054\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4273 - acc: 0.8071\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4270 - acc: 0.8113\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4262 - acc: 0.8088\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4251 - acc: 0.8102\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4261 - acc: 0.8070\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4273 - acc: 0.8076\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4270 - acc: 0.8085\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4255 - acc: 0.8103\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4230 - acc: 0.8118\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4286 - acc: 0.8069\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4255 - acc: 0.8087\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4259 - acc: 0.8073\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4240 - acc: 0.8104\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4219 - acc: 0.8124\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4219 - acc: 0.8110\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4227 - acc: 0.8081\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4211 - acc: 0.8113\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4216 - acc: 0.8121\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4248 - acc: 0.8091\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4228 - acc: 0.8121\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4231 - acc: 0.8106\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4216 - acc: 0.8102\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4220 - acc: 0.8120\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4196 - acc: 0.8118\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4357 - acc: 0.8038\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4373 - acc: 0.8027\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4370 - acc: 0.8014\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4345 - acc: 0.8038\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4397 - acc: 0.7989\n", "Epoch 6/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4385 - acc: 0.7978\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4352 - acc: 0.8033\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8056\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4330 - acc: 0.8038\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4339 - acc: 0.8071\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4325 - acc: 0.8060\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4313 - acc: 0.8021\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4317 - acc: 0.8056\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4325 - acc: 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24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4282 - acc: 0.8034\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4283 - acc: 0.8076\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4264 - acc: 0.8089\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4266 - acc: 0.8088\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4265 - acc: 0.8087\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4280 - acc: 0.8081\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4262 - acc: 0.8080\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4310 - acc: 0.8054\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4248 - acc: 0.8077\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4281 - acc: 0.8063\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8110\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4241 - acc: 0.8128\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4234 - acc: 0.8111\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4231 - acc: 0.8088\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8062\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8076\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4242 - acc: 0.8106\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4226 - acc: 0.8124\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8107\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4214 - acc: 0.8120\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4209 - acc: 0.8128\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4209 - acc: 0.8107\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4208 - acc: 0.8107\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4252 - acc: 0.8082\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4215 - acc: 0.8104\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4216 - acc: 0.8129\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4239 - acc: 0.8102\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4385 - acc: 0.8012\n", "Epoch 2/50\n", "7275/7275 [==============================] - 1s 78us/step - loss: 0.4378 - acc: 0.8011\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.4348 - acc: 0.8032\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 57us/step - loss: 0.4338 - acc: 0.8044\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4353 - acc: 0.8048\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4348 - acc: 0.8027\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4339 - acc: 0.8052\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.4339 - acc: 0.8067\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4356 - acc: 0.8034\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4332 - acc: 0.8032\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4337 - acc: 0.8077\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4332 - acc: 0.8044\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4308 - acc: 0.8073\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4315 - acc: 0.8073\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4290 - acc: 0.8060\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4299 - acc: 0.8037\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4306 - acc: 0.8107\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4284 - acc: 0.8080\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.4299 - acc: 0.8036\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.4275 - acc: 0.8102\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4317 - acc: 0.8047\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4289 - acc: 0.8049\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4309 - acc: 0.8067\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4271 - acc: 0.8093\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4290 - acc: 0.8080\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4273 - acc: 0.8085\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4269 - acc: 0.8085\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4303 - acc: 0.8059\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4242 - acc: 0.8087\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.4241 - acc: 0.8128\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4259 - acc: 0.8100\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4250 - acc: 0.8100\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4234 - acc: 0.8102\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4233 - acc: 0.8096\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8115\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8095\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8102\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4237 - acc: 0.8092\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 39/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4226 - acc: 0.8121\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4210 - acc: 0.8121\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4227 - acc: 0.8118\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4224 - acc: 0.8087\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4218 - acc: 0.8131\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.4195 - acc: 0.8146\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4191 - acc: 0.8132\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4202 - acc: 0.8110\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4196 - acc: 0.8150\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4231 - acc: 0.8082\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4206 - acc: 0.8136\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4184 - acc: 0.8137\n", " 0.8562789500772001\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4394 - acc: 0.8047\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.4430 - acc: 0.8016\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.4409 - acc: 0.8011\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.4397 - acc: 0.8022\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4364 - acc: 0.8034\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.4366 - acc: 0.8022\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4412 - acc: 0.8033\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 44us/step - loss: 0.4372 - acc: 0.8037\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4396 - acc: 0.8015\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4385 - acc: 0.8011\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4349 - acc: 0.8089\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4347 - acc: 0.8085\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4437 - acc: 0.8019\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4365 - acc: 0.8040\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4343 - acc: 0.8091\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4337 - acc: 0.8095\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4319 - acc: 0.8062\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4325 - acc: 0.8054\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4326 - acc: 0.8081\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4308 - acc: 0.8113\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4316 - acc: 0.8093\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4295 - acc: 0.8102\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4307 - acc: 0.8091\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4316 - acc: 0.8085\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4303 - acc: 0.8100\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4291 - acc: 0.8115\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4320 - acc: 0.8081\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4303 - acc: 0.8071\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4301 - acc: 0.8107\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4303 - acc: 0.8080\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8104\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8148\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4277 - acc: 0.8113\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4278 - acc: 0.8098\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4274 - acc: 0.8117\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4258 - acc: 0.8136\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4294 - acc: 0.8077\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8120\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4257 - acc: 0.8098\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4237 - acc: 0.8124\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4248 - acc: 0.8158\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4271 - acc: 0.8133\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4237 - acc: 0.8098\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4226 - acc: 0.8144\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4271 - acc: 0.8126\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4244 - acc: 0.8124\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4240 - acc: 0.8162\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4222 - acc: 0.8147\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4236 - acc: 0.8139\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4225 - acc: 0.8154\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4385 - acc: 0.8052\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4390 - acc: 0.8027\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4395 - acc: 0.8025\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4383 - acc: 0.8029\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4380 - acc: 0.8063\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4392 - acc: 0.8041\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4365 - acc: 0.8065\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4360 - acc: 0.8062\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4396 - acc: 0.8052\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4364 - acc: 0.8036\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4330 - acc: 0.8093\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4354 - acc: 0.8059\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4364 - acc: 0.8069\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4343 - acc: 0.8055\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4333 - acc: 0.8048\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4335 - acc: 0.8089\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4318 - acc: 0.8062\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4349 - acc: 0.8087\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4372 - acc: 0.8038\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4318 - acc: 0.8089\n", "Epoch 21/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 30us/step - loss: 0.4334 - acc: 0.8055\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4319 - acc: 0.8099\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4315 - acc: 0.8093\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4304 - acc: 0.8110\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4311 - acc: 0.8102\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4306 - acc: 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36/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4278 - acc: 0.8088\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4301 - acc: 0.8117\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4263 - acc: 0.8110\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4261 - acc: 0.8128\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4247 - acc: 0.8159\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4257 - acc: 0.8117\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4245 - acc: 0.8147\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4265 - acc: 0.8106\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4240 - acc: 0.8150\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4235 - acc: 0.8121\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4270 - acc: 0.8103\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4229 - acc: 0.8135\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4225 - acc: 0.8151\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4242 - acc: 0.8139\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4253 - acc: 0.8128\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4437 - acc: 0.7989\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4390 - acc: 0.8045\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4366 - acc: 0.8030\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4369 - acc: 0.8034\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4385 - acc: 0.8010\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4358 - acc: 0.8032\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 42us/step - loss: 0.4357 - acc: 0.8030\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4383 - acc: 0.8030\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4339 - acc: 0.8067\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4348 - acc: 0.8071\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4327 - acc: 0.8067\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4354 - acc: 0.8067\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4342 - acc: 0.8065\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4334 - acc: 0.8084\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4323 - acc: 0.8082\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4363 - acc: 0.8029\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4350 - acc: 0.8056\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4315 - acc: 0.8100\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4342 - acc: 0.8091\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4313 - acc: 0.8107\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4313 - acc: 0.8093\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4287 - acc: 0.8126\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4305 - acc: 0.8078\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4297 - acc: 0.8113\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4285 - acc: 0.8103\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.4285 - acc: 0.8110\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4279 - acc: 0.8131\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4302 - acc: 0.8084\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4281 - acc: 0.8091\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.4276 - acc: 0.8111\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4320 - acc: 0.8071\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4268 - acc: 0.8111\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4284 - acc: 0.8088\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4274 - acc: 0.8107\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4261 - acc: 0.8104\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4250 - acc: 0.8120\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4267 - acc: 0.8114\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4288 - acc: 0.8091\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4267 - acc: 0.8128\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4271 - acc: 0.8099\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4247 - acc: 0.8131\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4243 - acc: 0.8136\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4235 - acc: 0.8148\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4234 - acc: 0.8136\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4208 - acc: 0.8162\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4228 - acc: 0.8148\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4216 - acc: 0.8144\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4218 - acc: 0.8135\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4249 - acc: 0.8162\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4243 - acc: 0.8125\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4394 - acc: 0.8063\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4432 - acc: 0.8011\n", "Epoch 3/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 33us/step - loss: 0.4390 - acc: 0.8040\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.4383 - acc: 0.8029\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4358 - acc: 0.8065\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4376 - acc: 0.8051\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4373 - acc: 0.8021\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4369 - acc: 0.8069\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4394 - acc: 0.8010\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4389 - acc: 0.8018\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4348 - acc: 0.8066\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4350 - acc: 0.8030\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4319 - acc: 0.8055\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4366 - acc: 0.8027\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4312 - acc: 0.8054\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4346 - acc: 0.8065\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4349 - acc: 0.8055\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.4332 - acc: 0.8063\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4318 - acc: 0.8085\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4304 - acc: 0.8092\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 46us/step - loss: 0.4311 - acc: 0.8102\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4319 - acc: 0.8096\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4296 - acc: 0.8104\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8110\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4349 - acc: 0.8049\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4300 - acc: 0.8071\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4312 - acc: 0.8069\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4322 - acc: 0.8065\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4275 - acc: 0.8133\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4299 - acc: 0.8076\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8129\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4313 - acc: 0.8062\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4320 - acc: 0.8066\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4322 - acc: 0.8067\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4251 - acc: 0.8110\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4254 - acc: 0.8128\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4249 - acc: 0.8114\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4241 - acc: 0.8136\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4248 - acc: 0.8129\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4281 - acc: 0.8103\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4236 - acc: 0.8142\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4236 - acc: 0.8151\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4275 - acc: 0.8120\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4233 - acc: 0.8133\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4228 - acc: 0.8121\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4231 - acc: 0.8172\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4261 - acc: 0.8128\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4287 - acc: 0.8117\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4222 - acc: 0.8124\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4241 - acc: 0.8155\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4415 - acc: 0.7999\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4396 - acc: 0.8021\n", "Epoch 3/50\n", "7275/7275 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[==============================] - 0s 23us/step - loss: 0.4279 - acc: 0.8113\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4264 - acc: 0.8140\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4279 - acc: 0.8106\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4273 - acc: 0.8104\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4259 - acc: 0.8106\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4272 - acc: 0.8131\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 36/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4268 - acc: 0.8122\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4285 - acc: 0.8114\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4270 - acc: 0.8085\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4242 - acc: 0.8129\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4236 - acc: 0.8125\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4253 - acc: 0.8111\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4259 - acc: 0.8088\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4241 - acc: 0.8135\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4260 - acc: 0.8148\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4242 - acc: 0.8115\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4243 - acc: 0.8124\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4259 - acc: 0.8128\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4259 - acc: 0.8143\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4221 - acc: 0.8142\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4233 - acc: 0.8129\n", " 0.8699789231183983\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4424 - acc: 0.7999\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4419 - acc: 0.7973\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4413 - acc: 0.7997\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4393 - acc: 0.8004\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4392 - acc: 0.8010\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4378 - acc: 0.8032\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4393 - acc: 0.8004\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4385 - acc: 0.8018\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4432 - acc: 0.7993\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4361 - acc: 0.8014\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4374 - acc: 0.8022\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8037\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4372 - acc: 0.8032\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4360 - acc: 0.8022\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4363 - acc: 0.8011\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4371 - acc: 0.8034\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4350 - acc: 0.8055\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4347 - acc: 0.8059\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4312 - acc: 0.8114\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4336 - acc: 0.8070\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4319 - acc: 0.8063\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4315 - acc: 0.8060\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4322 - acc: 0.8055\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4309 - acc: 0.8077\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4314 - acc: 0.8047\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4340 - acc: 0.8055\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.4307 - acc: 0.8085\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4292 - acc: 0.8059\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4315 - acc: 0.8059\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4309 - acc: 0.8071\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4284 - acc: 0.8115\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4287 - acc: 0.8074\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4310 - acc: 0.8048\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8007\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4283 - acc: 0.8104\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4265 - acc: 0.8103\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4289 - acc: 0.8070\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4269 - acc: 0.8096\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8088\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4259 - acc: 0.8078\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8114\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4288 - acc: 0.8103\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4253 - acc: 0.8109\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4258 - acc: 0.8098\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4258 - acc: 0.8077\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4279 - acc: 0.8081\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4250 - acc: 0.8113\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4268 - acc: 0.8074\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8099\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4249 - acc: 0.8089\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4451 - acc: 0.7956\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4401 - acc: 0.7990\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4412 - acc: 0.7985\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4393 - acc: 0.8038\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4375 - acc: 0.8010\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4408 - acc: 0.8033\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4380 - acc: 0.7999\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4368 - acc: 0.8041\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4383 - acc: 0.8022\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4368 - acc: 0.8034\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4342 - acc: 0.8043\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4384 - acc: 0.8048\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4377 - acc: 0.8015\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4371 - acc: 0.8026\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4346 - acc: 0.8054\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4335 - acc: 0.8056\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4356 - acc: 0.8012\n", "Epoch 18/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4332 - acc: 0.8048\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4346 - acc: 0.8037\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.8045\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.8025\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4311 - acc: 0.8038\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4367 - acc: 0.8012\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4346 - acc: 0.8041\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8051\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8063\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4286 - acc: 0.8110\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8063\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4315 - acc: 0.8056\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4302 - acc: 0.8069\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4312 - acc: 0.8059\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8073\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4281 - acc: 0.8095\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4286 - acc: 0.8041\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4310 - acc: 0.8038\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4274 - acc: 0.8081\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4304 - acc: 0.8060\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8077\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4296 - acc: 0.8093\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8103\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4252 - acc: 0.8114\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4267 - acc: 0.8093\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4265 - acc: 0.8132\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4251 - acc: 0.8074\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8076\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4264 - acc: 0.8125\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4257 - acc: 0.8124\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8080\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4247 - acc: 0.8117\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4239 - acc: 0.8121\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4435 - acc: 0.7967\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4450 - acc: 0.7992\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4403 - acc: 0.7990\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4403 - acc: 0.7988\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4411 - acc: 0.7997\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4395 - acc: 0.8027\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4380 - acc: 0.8026\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4385 - acc: 0.8032\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4395 - acc: 0.8004\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8021\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4347 - acc: 0.8034\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4388 - acc: 0.8001\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4335 - acc: 0.8060\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4340 - acc: 0.8037\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8049\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4332 - acc: 0.8056\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4340 - acc: 0.8038\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4360 - acc: 0.8051\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4343 - acc: 0.8023\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4322 - acc: 0.8056\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4339 - acc: 0.8047\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4332 - acc: 0.8037\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4345 - acc: 0.8018\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4338 - acc: 0.8056\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4312 - acc: 0.8070\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4327 - acc: 0.8058\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4335 - acc: 0.8029\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4311 - acc: 0.8048\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4299 - acc: 0.8104\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8073\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8059\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4324 - acc: 0.8059\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8071\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4296 - acc: 0.8077\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4295 - acc: 0.8069\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4272 - acc: 0.8126\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8062\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4285 - acc: 0.8100\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4300 - acc: 0.8058\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4277 - acc: 0.8070\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4258 - acc: 0.8088\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4266 - acc: 0.8095\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4257 - acc: 0.8106\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8069\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4273 - acc: 0.8088\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8081\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4285 - acc: 0.8082\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8122\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8122\n", "Epoch 50/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8073\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4381 - acc: 0.8023\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4394 - acc: 0.7992\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4407 - acc: 0.7967\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4399 - acc: 0.7973\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4405 - acc: 0.8001\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4390 - acc: 0.8036\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4422 - acc: 0.8008\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4403 - acc: 0.7973\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4375 - acc: 0.8005\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4356 - acc: 0.8040\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4366 - acc: 0.8048\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.8054\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.8038\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4346 - acc: 0.8025\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4380 - acc: 0.7982\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4353 - acc: 0.8027\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4337 - acc: 0.8044\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4338 - acc: 0.8062\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4313 - acc: 0.8055\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4343 - acc: 0.8036\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8062\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4315 - acc: 0.8052\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4324 - acc: 0.8033\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4319 - acc: 0.8074\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4333 - acc: 0.8049\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4310 - acc: 0.8084\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4317 - acc: 0.8067\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4297 - acc: 0.8091\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4408 - acc: 0.7974\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4278 - acc: 0.8087\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4275 - acc: 0.8077\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4283 - acc: 0.8093\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4297 - acc: 0.8062\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4299 - acc: 0.8058\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4278 - acc: 0.8048\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4282 - acc: 0.8106\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4281 - acc: 0.8103\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4270 - acc: 0.8058\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4274 - acc: 0.8096\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4269 - acc: 0.8118\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8102\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8089\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4258 - acc: 0.8092\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4262 - acc: 0.8080\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4269 - acc: 0.8073\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4241 - acc: 0.8078\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4242 - acc: 0.8107\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4266 - acc: 0.8070\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4238 - acc: 0.8118\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4253 - acc: 0.8080\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4399 - acc: 0.8010\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4432 - acc: 0.7948\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4416 - acc: 0.8000\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4406 - acc: 0.7995\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4406 - acc: 0.7960\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4406 - acc: 0.7988\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4394 - acc: 0.8012\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4406 - acc: 0.7956\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4386 - acc: 0.8015\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4373 - acc: 0.8008\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4391 - acc: 0.8005\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4391 - acc: 0.7999\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4406 - acc: 0.7974\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8038\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4398 - acc: 0.8022\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4373 - acc: 0.7995\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4349 - acc: 0.8026\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.8043\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4335 - acc: 0.8032\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4374 - acc: 0.8033\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4335 - acc: 0.8071\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4318 - acc: 0.8073\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4345 - acc: 0.8047\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4328 - acc: 0.8048\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8084\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4315 - acc: 0.8069\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4332 - acc: 0.8045\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8085\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4365 - acc: 0.8011\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4301 - acc: 0.8089\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4300 - acc: 0.8049\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4295 - acc: 0.8089\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4306 - acc: 0.8080\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4295 - acc: 0.8045\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8066\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4300 - acc: 0.8081\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4272 - acc: 0.8074\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4302 - acc: 0.8063\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8047\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8069\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8029\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4297 - acc: 0.8052\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8080\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8065\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4254 - acc: 0.8106\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4261 - acc: 0.8071\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4250 - acc: 0.8118\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4257 - acc: 0.8104\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4293 - acc: 0.8087\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4230 - acc: 0.8132\n", " 0.8832193711246722\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4407 - acc: 0.8018\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4381 - acc: 0.8048\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4437 - acc: 0.8000\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4374 - acc: 0.8054\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4390 - acc: 0.8047\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4394 - acc: 0.7959\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4389 - acc: 0.8026\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.8034\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4374 - acc: 0.8027\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8073\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8044\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8071\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4341 - acc: 0.8071\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4349 - acc: 0.8052\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4348 - acc: 0.8069\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4324 - acc: 0.8060\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4336 - acc: 0.8078\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.8066\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4336 - acc: 0.8069\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8049\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4376 - acc: 0.8044\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4353 - acc: 0.8052\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4314 - acc: 0.8070\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4330 - acc: 0.8085\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4281 - acc: 0.8122\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4308 - acc: 0.8077\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4311 - acc: 0.8055\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4295 - acc: 0.8106\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4326 - acc: 0.8074\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4307 - acc: 0.8073\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4312 - acc: 0.8088\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4298 - acc: 0.8103\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4273 - acc: 0.8089\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4260 - acc: 0.8100\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4286 - acc: 0.8103\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4297 - acc: 0.8103\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4267 - acc: 0.8098\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4272 - acc: 0.8102\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8125\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4267 - acc: 0.8137\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4243 - acc: 0.8147\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4251 - acc: 0.8146\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8111\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8135\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4241 - acc: 0.8110\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4252 - acc: 0.8151\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4285 - acc: 0.8085\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8133\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4253 - acc: 0.8117\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4251 - acc: 0.8115\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4406 - acc: 0.8018\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4396 - acc: 0.8011\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4396 - acc: 0.8029\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4398 - acc: 0.8032\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4412 - acc: 0.7984\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4409 - acc: 0.7985\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4369 - acc: 0.8045\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.8071\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4381 - acc: 0.8040\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4366 - acc: 0.8040\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8033\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4368 - acc: 0.8043\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.8049\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4309 - acc: 0.8107\n", "Epoch 15/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4320 - acc: 0.8069\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8085\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4314 - acc: 0.8055\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8100\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4317 - acc: 0.8091\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4319 - acc: 0.8099\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8025\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4322 - acc: 0.8082\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8078\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4328 - acc: 0.8063\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4318 - acc: 0.8059\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4304 - acc: 0.8087\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4301 - acc: 0.8080\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4296 - acc: 0.8100\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4327 - acc: 0.8073\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8098\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4282 - acc: 0.8084\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4276 - acc: 0.8103\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4284 - acc: 0.8091\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4281 - acc: 0.8129\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8099\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4258 - acc: 0.8118\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8120\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4257 - acc: 0.8122\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8096\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4267 - acc: 0.8110\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8139\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8124\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8122\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8100\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4309 - acc: 0.8069\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8150\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4220 - acc: 0.8161\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8146\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4278 - acc: 0.8107\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8102\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4397 - acc: 0.8040\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4400 - acc: 0.8016\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4446 - acc: 0.7986\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4390 - acc: 0.8049\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4375 - acc: 0.8025\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4377 - acc: 0.8048\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4412 - acc: 0.8033\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4376 - acc: 0.8058\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4396 - acc: 0.8034\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4362 - acc: 0.8048\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4388 - acc: 0.8019\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4376 - acc: 0.8060\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8081\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4344 - acc: 0.8071\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4342 - acc: 0.8052\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4351 - acc: 0.8062\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8098\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8060\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4329 - acc: 0.8073\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8098\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8076\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8088\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4336 - acc: 0.8091\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4313 - acc: 0.8073\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4321 - acc: 0.8082\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4341 - acc: 0.8049\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4329 - acc: 0.8058\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4321 - acc: 0.8085\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4316 - acc: 0.8103\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8085\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4310 - acc: 0.8088\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4297 - acc: 0.8106\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8125\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4288 - acc: 0.8121\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4276 - acc: 0.8107\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8110\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4250 - acc: 0.8106\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4272 - acc: 0.8106\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4268 - acc: 0.8107\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4265 - acc: 0.8125\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4269 - acc: 0.8092\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4299 - acc: 0.8081\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4274 - acc: 0.8129\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8133\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4252 - acc: 0.8126\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8124\n", "Epoch 47/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 27us/step - loss: 0.4238 - acc: 0.8148\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4239 - acc: 0.8147\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8133\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4229 - acc: 0.8122\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4409 - acc: 0.8045\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4391 - acc: 0.8022\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4377 - acc: 0.8029\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4406 - acc: 0.8036\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4361 - acc: 0.8054\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8060\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4395 - acc: 0.8051\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8037\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4369 - acc: 0.8089\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4373 - acc: 0.8033\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4352 - acc: 0.8081\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4362 - acc: 0.8069\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4349 - acc: 0.8049\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4334 - acc: 0.8076\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4334 - acc: 0.8047\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4328 - acc: 0.8066\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.8047\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4383 - acc: 0.8027\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4374 - acc: 0.8062\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8100\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4313 - acc: 0.8073\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4309 - acc: 0.8082\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4304 - acc: 0.8087\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4344 - acc: 0.8052\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4304 - acc: 0.8113\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4345 - acc: 0.8062\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4300 - acc: 0.8074\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4279 - acc: 0.8103\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8085\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4343 - acc: 0.8052\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4301 - acc: 0.8074\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4290 - acc: 0.8092\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8126\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4282 - acc: 0.8078\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8111\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4325 - acc: 0.8088\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4267 - acc: 0.8135\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4262 - acc: 0.8104\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4271 - acc: 0.8158\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8114\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4238 - acc: 0.8146\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4240 - acc: 0.8159\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8120\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4253 - acc: 0.8133\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4314 - acc: 0.8081\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4248 - acc: 0.8128\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4239 - acc: 0.8133\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4232 - acc: 0.8135\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4221 - acc: 0.8120\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4237 - acc: 0.8133\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4401 - acc: 0.8034\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4385 - acc: 0.8025\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4378 - acc: 0.8034\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4383 - acc: 0.8022\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4365 - acc: 0.8065\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4381 - acc: 0.8037\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4376 - acc: 0.8048\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4374 - acc: 0.8041\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4364 - acc: 0.8062\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4379 - acc: 0.8040\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4382 - acc: 0.8040\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4423 - acc: 0.8026\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8077\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4368 - acc: 0.8059\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4387 - acc: 0.8018\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4337 - acc: 0.8091\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4342 - acc: 0.8045\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.8073\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4357 - acc: 0.8078\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4322 - acc: 0.8062\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4311 - acc: 0.8073\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4360 - acc: 0.8103\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4317 - acc: 0.8085\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4299 - acc: 0.8074\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4327 - acc: 0.8045\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4302 - acc: 0.8093\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8092\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4279 - acc: 0.8095\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4279 - acc: 0.8122\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4290 - acc: 0.8087\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4281 - acc: 0.8095\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4277 - acc: 0.8106\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4284 - acc: 0.8098\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4284 - acc: 0.8098\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8098\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8139\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8103\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4264 - acc: 0.8117\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4264 - acc: 0.8157\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4281 - acc: 0.8104\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4249 - acc: 0.8157\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4276 - acc: 0.8110\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4277 - acc: 0.8137\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4265 - acc: 0.8113\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4256 - acc: 0.8095\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4231 - acc: 0.8153\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4245 - acc: 0.8135\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4248 - acc: 0.8106\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4225 - acc: 0.8153\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4273 - acc: 0.8098\n", " 0.8722918657941817\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.7989\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4358 - acc: 0.8014\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8037\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4366 - acc: 0.8019\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4359 - acc: 0.8037\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4357 - acc: 0.8004\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4366 - acc: 0.8034\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4331 - acc: 0.8034\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4324 - acc: 0.8062\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4310 - acc: 0.8019\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4341 - acc: 0.8059\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4333 - acc: 0.8032\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4323 - acc: 0.8014\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4313 - acc: 0.8027\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4301 - acc: 0.8076\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4320 - acc: 0.8059\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4316 - acc: 0.8032\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4322 - acc: 0.8036\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4285 - acc: 0.8055\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4277 - acc: 0.8089\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4292 - acc: 0.8096\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8052\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4276 - acc: 0.8056\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4291 - acc: 0.8065\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4272 - acc: 0.8059\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8067\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4266 - acc: 0.8065\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4265 - acc: 0.8047\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4259 - acc: 0.8073\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8059\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4264 - acc: 0.8102\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4268 - acc: 0.8078\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4242 - acc: 0.8110\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4271 - acc: 0.8066\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8067\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8121\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4246 - acc: 0.8109\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4226 - acc: 0.8103\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4236 - acc: 0.8124\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4253 - acc: 0.8089\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4236 - acc: 0.8098\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4258 - acc: 0.8095\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4217 - acc: 0.8095\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4216 - acc: 0.8091\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4204 - acc: 0.8122\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4222 - acc: 0.8133\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4250 - acc: 0.8056\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4239 - acc: 0.8143\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4213 - acc: 0.8158\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4218 - acc: 0.8110\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4357 - acc: 0.8026\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8032\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4383 - acc: 0.8060\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4337 - acc: 0.8047\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4335 - acc: 0.8045\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4368 - acc: 0.8025\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8063\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4328 - acc: 0.8055\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4332 - acc: 0.8047\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4349 - acc: 0.8033\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4339 - acc: 0.8018\n", "Epoch 12/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8088\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8040\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4367 - acc: 0.8021\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4360 - acc: 0.8011\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8067\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4323 - acc: 0.8070\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4319 - acc: 0.8044\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4287 - acc: 0.8080\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4263 - acc: 0.8128\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4271 - acc: 0.8063\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4285 - acc: 0.8074\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8092\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4314 - acc: 0.8059\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4264 - acc: 0.8092\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8085\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4275 - acc: 0.8092\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8103\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4261 - acc: 0.8076\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4258 - acc: 0.8087\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4234 - acc: 0.8117\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4263 - acc: 0.8109\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4282 - acc: 0.8063\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4226 - acc: 0.8121\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8087\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4223 - acc: 0.8115\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4233 - acc: 0.8117\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4275 - acc: 0.8076\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4218 - acc: 0.8121\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4233 - acc: 0.8132\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4215 - acc: 0.8124\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4211 - acc: 0.8102\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4209 - acc: 0.8120\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4210 - acc: 0.8124\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4194 - acc: 0.8126\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4194 - acc: 0.8131\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4206 - acc: 0.8140\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4199 - acc: 0.8159\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4203 - acc: 0.8125\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4177 - acc: 0.8129\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4371 - acc: 0.7997\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4394 - acc: 0.7970\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4354 - acc: 0.8011\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4343 - acc: 0.8015\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4331 - acc: 0.8014\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4353 - acc: 0.8025\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4335 - acc: 0.8052\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4341 - acc: 0.8030\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4339 - acc: 0.8038\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4326 - acc: 0.8038\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4313 - acc: 0.8055\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4323 - acc: 0.8011\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4294 - acc: 0.8041\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4308 - acc: 0.8044\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4328 - acc: 0.8018\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4314 - acc: 0.8045\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4340 - acc: 0.8033\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4282 - acc: 0.8099\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8052\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8067\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4279 - acc: 0.8062\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4304 - acc: 0.8052\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8076\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4262 - acc: 0.8107\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4285 - acc: 0.8111\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8062\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4266 - acc: 0.8095\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4252 - acc: 0.8099\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8085\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8078\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4265 - acc: 0.8078\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4237 - acc: 0.8093\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4227 - acc: 0.8131\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4238 - acc: 0.8073\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4232 - acc: 0.8111\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4266 - acc: 0.8102\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8088\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4241 - acc: 0.8120\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4236 - acc: 0.8113\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4213 - acc: 0.8102\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4232 - acc: 0.8096\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8098\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4225 - acc: 0.8088\n", "Epoch 44/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4245 - acc: 0.8070\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4231 - acc: 0.8103\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8110\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4200 - acc: 0.8121\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4209 - acc: 0.8162\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4208 - acc: 0.8143\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4207 - acc: 0.8136\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4379 - acc: 0.7988\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4354 - acc: 0.8021\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4358 - acc: 0.8004\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4380 - acc: 0.8018\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4369 - acc: 0.8063\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4354 - acc: 0.8016\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4334 - acc: 0.8043\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4335 - acc: 0.8018\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4343 - acc: 0.8036\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4348 - acc: 0.8044\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4346 - acc: 0.8023\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4359 - acc: 0.7996\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4337 - acc: 0.8027\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4340 - acc: 0.8023\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8023\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8027\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4318 - acc: 0.8044\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8078\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4279 - acc: 0.8067\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4284 - acc: 0.8066\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4290 - acc: 0.8091\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4307 - acc: 0.8071\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4291 - acc: 0.8052\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4285 - acc: 0.8047\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4307 - acc: 0.8052\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4276 - acc: 0.8095\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4276 - acc: 0.8103\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4330 - acc: 0.8038\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8091\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4285 - acc: 0.8052\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4245 - acc: 0.8129\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4245 - acc: 0.8074\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4256 - acc: 0.8082\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8051\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4229 - acc: 0.8122\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4244 - acc: 0.8062\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4224 - acc: 0.8143\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8106\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4252 - acc: 0.8103\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8092\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4243 - acc: 0.8126\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4211 - acc: 0.8113\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4206 - acc: 0.8092\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4213 - acc: 0.8118\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4203 - acc: 0.8096\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4225 - acc: 0.8122\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4197 - acc: 0.8115\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4204 - acc: 0.8093\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4207 - acc: 0.8140\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4207 - acc: 0.8093\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4381 - acc: 0.8005\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4376 - acc: 0.8005\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4382 - acc: 0.8021\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4346 - acc: 0.8059\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4399 - acc: 0.8027\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4346 - acc: 0.8048\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.7989\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4329 - acc: 0.8047\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8049\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4311 - acc: 0.8054\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4322 - acc: 0.8056\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4372 - acc: 0.8007\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4322 - acc: 0.8041\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4321 - acc: 0.8058\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4300 - acc: 0.8054\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8063\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4269 - acc: 0.8070\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4285 - acc: 0.8045\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4296 - acc: 0.8062\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4284 - acc: 0.8067\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4303 - acc: 0.8054\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4293 - acc: 0.8051\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4266 - acc: 0.8082\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4304 - acc: 0.8058\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4283 - acc: 0.8084\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4269 - acc: 0.8091\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4284 - acc: 0.8100\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4256 - acc: 0.8076\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8080\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4255 - acc: 0.8120\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4231 - acc: 0.8109\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4249 - acc: 0.8132\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4237 - acc: 0.8107\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4225 - acc: 0.8124\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4240 - acc: 0.8129\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8078\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4246 - acc: 0.8107\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4228 - acc: 0.8093\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4214 - acc: 0.8128\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4218 - acc: 0.8109\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4219 - acc: 0.8136\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4221 - acc: 0.8109\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4237 - acc: 0.8118\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4247 - acc: 0.8120\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8118\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8092\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4209 - acc: 0.8131\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4197 - acc: 0.8128\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4190 - acc: 0.8148\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4216 - acc: 0.8118\n", " 0.8572960321544986\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4380 - acc: 0.7997\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4370 - acc: 0.8022\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4443 - acc: 0.7974\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4357 - acc: 0.8040\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4366 - acc: 0.8027\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4345 - acc: 0.8043\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4360 - acc: 0.8037\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4351 - acc: 0.8045\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4356 - acc: 0.8015\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4335 - acc: 0.8052\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4346 - acc: 0.8012\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4352 - acc: 0.8018\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4338 - acc: 0.8065\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8051\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4340 - acc: 0.8073\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4321 - acc: 0.8047\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4306 - acc: 0.8077\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4321 - acc: 0.8084\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4290 - acc: 0.8071\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4301 - acc: 0.8076\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4291 - acc: 0.8089\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4304 - acc: 0.8073\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4309 - acc: 0.8073\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4308 - acc: 0.8081\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8062\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8089\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4298 - acc: 0.8109\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4257 - acc: 0.8120\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4262 - acc: 0.8073\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4253 - acc: 0.8136\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8062\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8098\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4295 - acc: 0.8093\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4275 - acc: 0.8085\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4269 - acc: 0.8081\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8126\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8110\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4233 - acc: 0.8107\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4244 - acc: 0.8113\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4270 - acc: 0.8120\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4221 - acc: 0.8121\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4226 - acc: 0.8117\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4259 - acc: 0.8071\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4221 - acc: 0.8133\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4231 - acc: 0.8118\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4257 - acc: 0.8106\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4228 - acc: 0.8146\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4227 - acc: 0.8131\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4214 - acc: 0.8133\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4215 - acc: 0.8132\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4419 - acc: 0.8021\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4378 - acc: 0.8012\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4379 - acc: 0.8029\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4368 - acc: 0.8033\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4373 - acc: 0.8003\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4360 - acc: 0.8012\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4376 - acc: 0.8036\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4375 - acc: 0.8000\n", "Epoch 9/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 26us/step - loss: 0.4362 - acc: 0.8015\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4344 - acc: 0.8043\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4344 - acc: 0.8011\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4350 - acc: 0.8019\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4361 - acc: 0.8018\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4336 - acc: 0.8059\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4312 - acc: 0.8071\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4323 - acc: 0.8056\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4324 - acc: 0.8085\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4338 - acc: 0.8026\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4326 - acc: 0.8033\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4303 - acc: 0.8059\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4300 - acc: 0.8078\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8043\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4306 - acc: 0.8076\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4328 - acc: 0.8037\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8073\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4306 - acc: 0.8085\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8104\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4275 - acc: 0.8076\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8063\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4273 - acc: 0.8069\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8091\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8060\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4273 - acc: 0.8107\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4274 - acc: 0.8110\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4268 - acc: 0.8093\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4270 - acc: 0.8091\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4268 - acc: 0.8071\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4258 - acc: 0.8111\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4259 - acc: 0.8136\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4242 - acc: 0.8093\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8111\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4287 - acc: 0.8074\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8114\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4244 - acc: 0.8099\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4295 - acc: 0.8080\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4240 - acc: 0.8148\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4249 - acc: 0.8125\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4248 - acc: 0.8087\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4213 - acc: 0.8155\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4227 - acc: 0.8159\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4404 - acc: 0.7985\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4367 - acc: 0.8044\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4384 - acc: 0.7989\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.8021\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4349 - acc: 0.8060\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4364 - acc: 0.8051\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4354 - acc: 0.8016\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4368 - acc: 0.7992\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4344 - acc: 0.8004\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4350 - acc: 0.8051\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8027\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4336 - acc: 0.8044\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4341 - acc: 0.8047\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4316 - acc: 0.8069\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8055\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4324 - acc: 0.8043\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4319 - acc: 0.8056\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4299 - acc: 0.8069\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4317 - acc: 0.8033\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4334 - acc: 0.8001\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8069\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4307 - acc: 0.8076\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4277 - acc: 0.8084\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4279 - acc: 0.8081\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4280 - acc: 0.8111\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8071\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4272 - acc: 0.8077\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4286 - acc: 0.8065\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4309 - acc: 0.8102\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4265 - acc: 0.8106\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4289 - acc: 0.8082\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8096\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4265 - acc: 0.8110\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4252 - acc: 0.8125\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4268 - acc: 0.8089\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4247 - acc: 0.8111\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8029\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4250 - acc: 0.8120\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4261 - acc: 0.8049\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4252 - acc: 0.8107\n", "Epoch 41/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 27us/step - loss: 0.4276 - acc: 0.8102\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4257 - acc: 0.8099\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4279 - acc: 0.8059\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4220 - acc: 0.8122\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4269 - acc: 0.8088\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4235 - acc: 0.8139\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4223 - acc: 0.8124\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4199 - acc: 0.8118\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8139\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4206 - acc: 0.8151\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4368 - acc: 0.8037\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 37us/step - loss: 0.4379 - acc: 0.8018\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4378 - acc: 0.8010\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4364 - acc: 0.8038\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4357 - acc: 0.8029\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4346 - acc: 0.8025\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4368 - acc: 0.8041\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4358 - acc: 0.8018\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4336 - acc: 0.8004\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4345 - acc: 0.8048\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4349 - acc: 0.8022\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4330 - acc: 0.8033\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4349 - acc: 0.8018\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4339 - acc: 0.8008\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4326 - acc: 0.8066\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4320 - acc: 0.8063\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4361 - acc: 0.8029\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4301 - acc: 0.8063\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4292 - acc: 0.8081\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4382 - acc: 0.8011\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4300 - acc: 0.8082\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8093\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4312 - acc: 0.8070\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.4302 - acc: 0.8082\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4333 - acc: 0.8085\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4259 - acc: 0.8103\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4321 - acc: 0.8055\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4305 - acc: 0.8087\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4271 - acc: 0.8093\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 52us/step - loss: 0.4301 - acc: 0.8080\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 45us/step - loss: 0.4304 - acc: 0.8044\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4277 - acc: 0.8091\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4280 - acc: 0.8089\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4270 - acc: 0.8098\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 52us/step - loss: 0.4259 - acc: 0.8120\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 49us/step - loss: 0.4259 - acc: 0.8126\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 56us/step - loss: 0.4269 - acc: 0.8113\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.4274 - acc: 0.8110\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.4261 - acc: 0.8073\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.4224 - acc: 0.8137\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4240 - acc: 0.8124\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4239 - acc: 0.8100\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4247 - acc: 0.8099\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4253 - acc: 0.8098\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4225 - acc: 0.8147\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4225 - acc: 0.8114\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4213 - acc: 0.8139\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4211 - acc: 0.8158\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4256 - acc: 0.8100\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4237 - acc: 0.8098\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4405 - acc: 0.8021\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4385 - acc: 0.8007\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4370 - acc: 0.8016\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4366 - acc: 0.8005\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4384 - acc: 0.8000\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4382 - acc: 0.8027\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4405 - acc: 0.7990\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4337 - acc: 0.8027\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4351 - acc: 0.8030\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4346 - acc: 0.8030\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4363 - acc: 0.8005\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4352 - acc: 0.8054\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4349 - acc: 0.8026\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4362 - acc: 0.8012\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4343 - acc: 0.8047\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4326 - acc: 0.8045\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4310 - acc: 0.8040\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4302 - acc: 0.8060\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4308 - acc: 0.8047\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4353 - acc: 0.8027\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4303 - acc: 0.8038\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4275 - acc: 0.8070\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4321 - acc: 0.8078\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 24/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4301 - acc: 0.8058\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4281 - acc: 0.8081\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4305 - acc: 0.8098\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4291 - acc: 0.8082\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4283 - acc: 0.8073\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4286 - acc: 0.8074\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4273 - acc: 0.8089\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 38us/step - loss: 0.4271 - acc: 0.8065\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 48us/step - loss: 0.4261 - acc: 0.8100\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 51us/step - loss: 0.4249 - acc: 0.8114\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4267 - acc: 0.8078\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 63us/step - loss: 0.4256 - acc: 0.8109\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 40us/step - loss: 0.4275 - acc: 0.8077\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 53us/step - loss: 0.4262 - acc: 0.8104\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 43us/step - loss: 0.4286 - acc: 0.8071\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4251 - acc: 0.8117\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4274 - acc: 0.8093\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4267 - acc: 0.8081\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4261 - acc: 0.8073\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8103\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4226 - acc: 0.8121\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8121\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4221 - acc: 0.8117\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8114\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4248 - acc: 0.8109\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4234 - acc: 0.8107\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4240 - acc: 0.8115\n", " 0.8687535230252679\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4377 - acc: 0.8037\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4376 - acc: 0.8034\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4368 - acc: 0.8021\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4368 - acc: 0.8067\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4373 - acc: 0.8026\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4382 - acc: 0.8038\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4361 - acc: 0.8067\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4354 - acc: 0.8029\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4346 - acc: 0.8041\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4364 - acc: 0.8049\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4360 - acc: 0.8048\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4335 - acc: 0.8070\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4350 - acc: 0.8040\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4331 - acc: 0.8058\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4324 - acc: 0.8048\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4336 - acc: 0.8047\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4323 - acc: 0.8077\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4348 - acc: 0.8054\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4347 - acc: 0.8048\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4308 - acc: 0.8085\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4322 - acc: 0.8074\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4319 - acc: 0.8054\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4282 - acc: 0.8092\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4298 - acc: 0.8110\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4298 - acc: 0.8100\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4306 - acc: 0.8066\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4281 - acc: 0.8113\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4266 - acc: 0.8129\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4314 - acc: 0.8082\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8071\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4263 - acc: 0.8126\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4265 - acc: 0.8135\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4314 - acc: 0.8049\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4270 - acc: 0.8085\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4298 - acc: 0.8091\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4253 - acc: 0.8104\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4244 - acc: 0.8139\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4250 - acc: 0.8131\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4237 - acc: 0.8128\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4270 - acc: 0.8106\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4246 - acc: 0.8126\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4253 - acc: 0.8136\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4220 - acc: 0.8154\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4245 - acc: 0.8125\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4237 - acc: 0.8125\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4261 - acc: 0.8124\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4227 - acc: 0.8113\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4220 - acc: 0.8120\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4217 - acc: 0.8129\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4224 - acc: 0.8144\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4397 - acc: 0.8004\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4419 - acc: 0.8019\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4385 - acc: 0.8018\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4370 - acc: 0.8019\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 34us/step - loss: 0.4385 - acc: 0.8033\n", "Epoch 6/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 27us/step - loss: 0.4354 - acc: 0.8063\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4368 - acc: 0.8034\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4359 - acc: 0.8060\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4354 - acc: 0.8044\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4355 - acc: 0.8047\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4341 - acc: 0.8056\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4334 - acc: 0.8089\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4356 - acc: 0.8081\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4347 - acc: 0.8092\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4315 - acc: 0.8074\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4365 - acc: 0.8048\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4323 - acc: 0.8084\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4321 - acc: 0.8081\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4295 - acc: 0.8114\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4333 - acc: 0.8055\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4302 - acc: 0.8078\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4293 - acc: 0.8122\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8104\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4303 - acc: 0.8067\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4319 - acc: 0.8099\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4277 - acc: 0.8109\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4313 - acc: 0.8081\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4306 - acc: 0.8062\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4276 - acc: 0.8115\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4299 - acc: 0.8074\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4287 - acc: 0.8099\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4290 - acc: 0.8071\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4265 - acc: 0.8154\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8089\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4271 - acc: 0.8110\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4269 - acc: 0.8093\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4243 - acc: 0.8148\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4280 - acc: 0.8107\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4247 - acc: 0.8132\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4255 - acc: 0.8122\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4252 - acc: 0.8114\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4290 - acc: 0.8117\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4228 - acc: 0.8121\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4229 - acc: 0.8118\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4233 - acc: 0.8128\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4243 - acc: 0.8107\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4220 - acc: 0.8115\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4242 - acc: 0.8092\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4243 - acc: 0.8132\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4276 - acc: 0.8104\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4418 - acc: 0.8015\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4395 - acc: 0.8043\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4372 - acc: 0.8047\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4400 - acc: 0.8011\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4410 - acc: 0.8019\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4388 - acc: 0.8033\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4347 - acc: 0.8062\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4388 - acc: 0.8095\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4354 - acc: 0.8056\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4335 - acc: 0.8085\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4327 - acc: 0.8069\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4331 - acc: 0.8051\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4383 - acc: 0.8033\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8058\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4328 - acc: 0.8063\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4327 - acc: 0.8067\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4334 - acc: 0.8066\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4401 - acc: 0.7993\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4316 - acc: 0.8056\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4299 - acc: 0.8087\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4301 - acc: 0.8103\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4325 - acc: 0.8078\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4329 - acc: 0.8084\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4292 - acc: 0.8098\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4280 - acc: 0.8082\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4283 - acc: 0.8109\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4284 - acc: 0.8078\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4270 - acc: 0.8103\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4302 - acc: 0.8092\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4305 - acc: 0.8084\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4316 - acc: 0.8076\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4272 - acc: 0.8117\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4272 - acc: 0.8107\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 36us/step - loss: 0.4263 - acc: 0.8129\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4276 - acc: 0.8100\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4249 - acc: 0.8139\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4302 - acc: 0.8106\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4255 - acc: 0.8121\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 39/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4246 - acc: 0.8126\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8117\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4237 - acc: 0.8140\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4253 - acc: 0.8091\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4226 - acc: 0.8114\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4280 - acc: 0.8070\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4238 - acc: 0.8129\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8131\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4247 - acc: 0.8133\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 33us/step - loss: 0.4234 - acc: 0.8164\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 50us/step - loss: 0.4254 - acc: 0.8111\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4217 - acc: 0.8157\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4393 - acc: 0.7995\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4363 - acc: 0.8048\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4371 - acc: 0.8043\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4381 - acc: 0.8029\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4372 - acc: 0.8048\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4348 - acc: 0.8047\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4358 - acc: 0.8047\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 39us/step - loss: 0.4356 - acc: 0.8034\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4363 - acc: 0.8038\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4359 - acc: 0.8036\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4336 - acc: 0.8043\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4381 - acc: 0.8001\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4352 - acc: 0.8043\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4348 - acc: 0.8049\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4328 - acc: 0.8054\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4324 - acc: 0.8071\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4334 - acc: 0.8074\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4317 - acc: 0.8066\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4302 - acc: 0.8089\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4308 - acc: 0.8082\n", "Epoch 21/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4348 - acc: 0.8062\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4312 - acc: 0.8070\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4303 - acc: 0.8074\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4300 - acc: 0.8081\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4320 - acc: 0.8100\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4304 - acc: 0.8098\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4312 - acc: 0.8044\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4278 - acc: 0.8115\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4276 - acc: 0.8073\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 29us/step - loss: 0.4285 - acc: 0.8106\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4258 - acc: 0.8104\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4271 - acc: 0.8078\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4254 - acc: 0.8109\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 32us/step - loss: 0.4298 - acc: 0.8069\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4271 - acc: 0.8085\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4338 - acc: 0.8074\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4269 - acc: 0.8103\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4300 - acc: 0.8109\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4255 - acc: 0.8096\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4244 - acc: 0.8139\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4265 - acc: 0.8111\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4253 - acc: 0.8136\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4238 - acc: 0.8104\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4239 - acc: 0.8139\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4225 - acc: 0.8128\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4215 - acc: 0.8180\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4245 - acc: 0.8093\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4243 - acc: 0.8135\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4215 - acc: 0.8168\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4207 - acc: 0.8114\n", ">>\n", ".\n", "Epoch 1/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4404 - acc: 0.8011\n", "Epoch 2/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4373 - acc: 0.8045\n", "Epoch 3/50\n", "7275/7275 [==============================] - 0s 22us/step - loss: 0.4384 - acc: 0.8018\n", "Epoch 4/50\n", "7275/7275 [==============================] - 0s 23us/step - loss: 0.4381 - acc: 0.8032\n", "Epoch 5/50\n", "7275/7275 [==============================] - 0s 24us/step - loss: 0.4384 - acc: 0.8073\n", "Epoch 6/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4377 - acc: 0.8047\n", "Epoch 7/50\n", "7275/7275 [==============================] - 0s 31us/step - loss: 0.4377 - acc: 0.8041\n", "Epoch 8/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4364 - acc: 0.8030\n", "Epoch 9/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4389 - acc: 0.8018\n", "Epoch 10/50\n", "7275/7275 [==============================] - 0s 35us/step - loss: 0.4348 - acc: 0.8081\n", "Epoch 11/50\n", "7275/7275 [==============================] - 0s 41us/step - loss: 0.4362 - acc: 0.8041\n", "Epoch 12/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4364 - acc: 0.8045\n", "Epoch 13/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4384 - acc: 0.7999\n", "Epoch 14/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4369 - acc: 0.8025\n", "Epoch 15/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4345 - acc: 0.8070\n", "Epoch 16/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4336 - acc: 0.8069\n", "Epoch 17/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4322 - acc: 0.8070\n", "Epoch 18/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4345 - acc: 0.8048\n", "Epoch 19/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4334 - acc: 0.8059\n", "Epoch 20/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4331 - acc: 0.8032\n", "Epoch 21/50\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "7275/7275 [==============================] - 0s 25us/step - loss: 0.4316 - acc: 0.8082\n", "Epoch 22/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4288 - acc: 0.8100\n", "Epoch 23/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4290 - acc: 0.8096\n", "Epoch 24/50\n", "7275/7275 [==============================] - 0s 27us/step - loss: 0.4304 - acc: 0.8110\n", "Epoch 25/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4289 - acc: 0.8122\n", "Epoch 26/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4318 - acc: 0.8100\n", "Epoch 27/50\n", "7275/7275 [==============================] - 0s 28us/step - loss: 0.4344 - acc: 0.8067\n", "Epoch 28/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4306 - acc: 0.8082\n", "Epoch 29/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4282 - acc: 0.8095\n", "Epoch 30/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4270 - acc: 0.8102\n", "Epoch 31/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4363 - acc: 0.8022\n", "Epoch 32/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4305 - acc: 0.8089\n", "Epoch 33/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4296 - acc: 0.8092\n", "Epoch 34/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8115\n", "Epoch 35/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4278 - acc: 0.8110\n", "Epoch 36/50\n", "7275/7275 [==============================] - 0s 30us/step - loss: 0.4280 - acc: 0.8085\n", "Epoch 37/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8143\n", "Epoch 38/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4275 - acc: 0.8109\n", "Epoch 39/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4260 - acc: 0.8091\n", "Epoch 40/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4265 - acc: 0.8111\n", "Epoch 41/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4266 - acc: 0.8125\n", "Epoch 42/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4277 - acc: 0.8111\n", "Epoch 43/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4230 - acc: 0.8136\n", "Epoch 44/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4228 - acc: 0.8139\n", "Epoch 45/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4235 - acc: 0.8122\n", "Epoch 46/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4234 - acc: 0.8117\n", "Epoch 47/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4256 - acc: 0.8147\n", "Epoch 48/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4273 - acc: 0.8151\n", "Epoch 49/50\n", "7275/7275 [==============================] - 0s 25us/step - loss: 0.4237 - acc: 0.8104\n", "Epoch 50/50\n", "7275/7275 [==============================] - 0s 26us/step - loss: 0.4263 - acc: 0.8081\n", " 0.8692743180648482\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "array([0.08044943, 0.07390783, 0.08255558, ..., 0.67880201, 0.07709893,\n", " 0.10023439])" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Logistic regression (SGD)\n", "cv = StratifiedKFold(n_splits=10)\n", "results = np.zeros_like(y, dtype=float)\n", "\n", "tprs = []\n", "aucs = []\n", "mean_fpr = np.linspace(0, 1, 100)\n", "\n", "i = 0\n", "for train, test in cv.split(X, y):\n", " keras.backend.clear_session()\n", " prbs=[]\n", " \n", " quant_trans = sklearn.preprocessing.QuantileTransformer(output_distribution='uniform').fit(X[train,:])\n", " for mod in range(5):\n", " print('>>')\n", " curr_try = 0\n", " while curr_try <10:\n", " print('.')\n", "\n", " model = Sequential()\n", " model.add(Dense(1, activation='sigmoid'))\n", " # Compile model\n", " opt = keras.optimizers.Adam(epsilon=None, amsgrad=True)\n", " model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])\n", " \n", " # Fit the model\n", " history = model.fit(quant_trans.transform(X[train,:]), y[train], epochs=50, batch_size=64, verbose=0)\n", " if history.history['acc'][-1] > 0.53:\n", " break\n", " else:\n", " curr_try += 1\n", "\n", " # Fit the model\n", " model.fit(quant_trans.transform(X[train,:]), y[train], epochs=50, batch_size=64, verbose=1)\n", " \n", " # evaluate the model\n", " probas_ = model.predict(quant_trans.transform(X[test,:]))\n", " prbs.append(probas_)\n", " # Average the predictions\n", " probas_ = np.mean(np.hstack(prbs), axis=1)\n", " results[test] = probas_\n", " \n", " # Compute ROC curve and area the curve\n", " fpr, tpr, thresholds = roc_curve(y[test], probas_[ :])\n", " print(' ' + str(auc(fpr, tpr)))\n", " tprs.append(interp(mean_fpr, fpr, tpr))\n", " tprs[-1][0] = 0.0\n", " roc_auc = auc(fpr, tpr)\n", " aucs.append(roc_auc)\n", " plt.plot(fpr, tpr, lw=1, alpha=0.3,\n", " label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n", "\n", " i += 1\n", "plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n", " label='Chance', alpha=.8)\n", "\n", "mean_tpr = np.mean(tprs, axis=0)\n", "mean_tpr[-1] = 1.0\n", "mean_auc = auc(mean_fpr, mean_tpr)\n", "std_auc = np.std(aucs)\n", "plt.plot(mean_fpr, mean_tpr, color='b',\n", " label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n", " lw=2, alpha=.8)\n", "\n", "std_tpr = np.std(tprs, axis=0)\n", "tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n", "tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n", "plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n", " label=r'$\\pm$ 1 std. dev.')\n", "\n", "plt.xlim([-0.05, 1.05])\n", "plt.ylim([-0.05, 1.05])\n", "plt.xlabel('False Positive Rate')\n", "plt.ylabel('True Positive Rate')\n", "plt.title('Receiver operating characteristic example')\n", "plt.legend(loc=\"lower right\")\n", "plt.show()\n", "results" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "df_results = pd.DataFrame(data={\"name\": names, 'pred': results})\n", "df_results.to_csv('/home/drewe/notebooks/genotox/pred.lr.v4.norm.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD8CAYAAAB5Pm/hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAEo5JREFUeJzt3X+sZHdZx/H3RwpoFWxht1i7XbeaQkSiobkhRRNcLWCppMsfxRQFFqxuBEQEFYr80UUlQVFREgQXWykGKbWi3RgQm8paNbSy5UcpLchasF27sotA/YEK1cc/5hQvy/0xd878/M77lWzuzJkzM8+59+5nnnnOmXNTVUiS2vV1sy5AkjRZBr0kNc6gl6TGGfSS1DiDXpIaZ9BLUuMMeklqnEEvSY0z6CWpcafMugCAbdu21a5du2ZdhiQtlFtvvfWzVbV9s/XmIuh37drF4cOHZ12GJC2UJP84zHqObiSpcQa9JDXOoJekxhn0ktQ4g16SGmfQS1LjDHpJapxBL0mNM+glqXFz8clYSVoE+/evfXne2dFLUuMMeklqnEEvSY0z6CWpcQa9JDXOoJekxhn0ktQ4g16SGmfQS1LjDHpJapxBL0mN2zTok1yV5HiS29e47eeTVJJt3fUkeUOSI0luS3LeJIqWJA1vmI7+rcCFJy9McjbwFODuVYufBpzb/dsHvKl/iZKkPjYN+qq6CfjcGje9Hng5UKuW7QHeVgM3A6clOXMslUqSRjLSjD7JxcA/VdVHTrrpLOCeVdePdsskSTOy5fPRJzkVeBXw1LVuXmNZrbGMJPsYjHfYuXPnVsuQJA1plI7+O4BzgI8k+TSwA/hgkm9h0MGfvWrdHcC9az1IVR2oqpWqWtm+ffsIZUiShrHloK+qj1bVGVW1q6p2MQj386rqn4GDwHO7o2/OB+6rqmPjLVmStBXDHF75DuD9wGOSHE1y2Qarvxu4CzgCvAV44ViqlCSNbNMZfVU9a5Pbd626XMCL+pclSYtvXv7GrJ+MlaTGGfSS1DiDXpIaZ9BLUuMMeklqnEEvSY0z6CWpcQa9JDXOoJekxhn0ktQ4g16SGrfl89FLkubnPDbDsKOXpMbZ0UvSKid35/PerQ/Djl6SGmdHL0k9zfu83o5ekhpn0EtS4xzdSNIYLeToJslVSY4nuX3Vstcl+XiS25L8SZLTVt32yiRHknwiyQ9NqnBJ0nCGGd28FbjwpGU3AI+rqu8G/h54JUCSxwKXAt/V3ed3kjxobNVKkrZs06CvqpuAz5207C+q6v7u6s3Aju7yHuCaqvrvqvoUcAR4whjrlSRt0Th2xv448J7u8lnAPatuO9ot+xpJ9iU5nOTwiRMnxlCGJGktvYI+yauA+4G3P7BojdVqrftW1YGqWqmqle3bt/cpQ5K0gZGPukmyF3g6cEFVPRDmR4GzV622A7h39PImZN4/3SBJYzRSR5/kQuAVwMVV9cVVNx0ELk3y0CTnAOcCf9e/TEnSqDbt6JO8A9gNbEtyFLiCwVE2DwVuSAJwc1X9VFV9LMm1wB0MRjovqqr/mVTxkjQOrb+x3zToq+pZayy+coP1XwO8pk9RkqTx8RQIktQ4T4GwmjtpJTXIoB+GLwCSFpijG0lqXLsdfYt/D0ySRtBu0A/LFwBJUzDLCbCjG0lqnEEvSY1zdLMeRzpS05bpv7gdvSQ1zqCXpMa1NbpZpvdikqaihVixo5ekxhn0ktQ4g16SGmfQS1Lj2toZu5EW9qhI6mVZY8COXpIat2nQJ7kqyfEkt69a9ogkNyT5ZPf19G55krwhyZEktyU5b5LFS5I2N0xH/1bgwpOWXQ7cWFXnAjd21wGeBpzb/dsHvGk8ZUqSRrVp0FfVTcDnTlq8B7i6u3w18IxVy99WAzcDpyU5c1zFSpK2btQZ/aOq6hhA9/WMbvlZwD2r1jvaLZMkzci4j7rJGstqzRWTfQzGO+zcuXPMZUyJf0tW0gIYtaP/zAMjme7r8W75UeDsVevtAO5d6wGq6kBVrVTVyvbt20csQ5K0mVGD/iCwt7u8F7h+1fLndkffnA/c98CIR5I0G5uObpK8A9gNbEtyFLgCeC1wbZLLgLuBZ3arvxu4CDgCfBF4/gRqliRtwaZBX1XPWuemC9ZYt4AX9S1KkjQ+fjJWkhq3POe6mSaPxpE0R+zoJalxBr0kNc6gl6TGGfSS1DiDXpIa51E34+LRNZLmlB29JDXOoJekxjm62SpHNJIWjEE/K356VtKUGPSSmmMf9dWc0UtS4wx6SWqcQS9JjXNGP2kOC6WZ8r+dHb0kNa9XR5/kpcBPAAV8lMHfiD0TuAZ4BPBB4DlV9aWedUrShuzc1zdy0Cc5C/gZ4LFV9Z9JrgUuZfDHwV9fVdckeTNwGfCmsVQraWk49RyfvjP6U4BvSPJl4FTgGPCDwI92t18N7MegH/C3VdIMjDyjr6p/An4duJtBwN8H3Ap8oaru71Y7CpzVt0hJ0uhGDvokpwN7gHOAbwW+EXjaGqvWOvffl+RwksMnTpwYtQxJ0ib6HHXzZOBTVXWiqr4MvAv4XuC0JA+MhHYA965156o6UFUrVbWyffv2HmVIkjbSJ+jvBs5PcmqSABcAdwDvAy7p1tkLXN+vRElSH31m9LcA1zE4hPKj3WMdAF4BvCzJEeCRwJVjqFOSNKJeR91U1RXAFSctvgt4Qp/HlSSNj6dAkLSwPGJ5OJ4CQZIaZ9BLUuMc3bTKz49L6hj0kuaGPclkOLqRpMYZ9JLUOEc3i85ZvJaMv+ZbZ9DPs/V+o/1Nl7QFjm4kqXEGvSQ1ztHNPHDOLmmC7OglqXEGvSQ1ztGNpLGaxCTSiWY/Br2kqXBX1Ow4upGkxtnRS5oYO/f50KujT3JakuuSfDzJnUmemOQRSW5I8snu6+njKlaStHV9O/rfBv68qi5J8hDgVOAXgRur6rVJLgcuZ/AHwzWMPi2Q7ZOkNYzc0Sd5OPAk4EqAqvpSVX0B2ANc3a12NfCMvkVKkkbXp6P/duAE8PtJvge4FXgJ8KiqOgZQVceSnNG/TH0VO3dJW9BnRn8KcB7wpqp6PPAfDMY0Q0myL8nhJIdPnDjRowxJ0kb6dPRHgaNVdUt3/ToGQf+ZJGd23fyZwPG17lxVB4ADACsrK9WjDs0bD5huij/OxTdyR19V/wzck+Qx3aILgDuAg8Debtle4PpeFUqSeul71M2Lgbd3R9zcBTyfwYvHtUkuA+4GntnzOSRJPfQK+qr6MLCyxk0X9HlcScvDcdDkeQoESWqcp0DQwKT2uLknT5o5O3pJatzid/R2iVvjycKlpWNHL0mNM+glqXGLP7qRpAUz7WMUDHpJI/GAqsXh6EaSGmdHvwwmcXSNLVxzpvnj9ddnuuzoJalxBr0kNc6gl6TGOaNfZg5Kl4a7V5abHb0kNc6OXhtbr/2zLZQWhh29JDXOjl5aYr4xWw4GvTSnTg7heQ7lea5NYxjdJHlQkg8l+bPu+jlJbknyySTv7P5wuCRpRsYxo38JcOeq678KvL6qzgU+D1w2hudQa/bv//9/kiaqV9An2QH8MPB73fUAPwhc161yNfCMPs8hSeqnb0f/W8DLgf/trj8S+EJV3d9dPwqctdYdk+xLcjjJ4RMnTvQsQ5K0npGDPsnTgeNVdevqxWusWmvdv6oOVNVKVa1s37591DIkSZvoc9TN9wEXJ7kI+Hrg4Qw6/NOSnNJ19TuAe/uXKWkY4zrVgbtO2jJy0FfVK4FXAiTZDfx8Vf1Ykj8CLgGuAfYC14+hTi27Bj6hO6nzzUzzW7BA326tMonj6F8BXJPkV4APAVdO4Dm0iIYJa5NEGruxBH1VHQIOdZfvAp4wjseVJPXnJ2O12Hw3sGV+m5aPQa+vNcskmMTexGEexxcMNcygl2bM1xVNmqcplqTG2dFLC8LOX6My6DW/JpRsU9sN4Nxfc8LRjSQ1zo5eGrOvNO+HdrN/96EZViINGPTSGGx1MuMkR9Nk0EsnG2a2vn8/HNo9uLx790TL2dChQ/9/eVx1TOIxNVPO6CWpcXb0al/Po1/WvMsD3fwo7Jg1ZQa92rHVED90CPYfWvuhHgjy1Q+5OqC3avWop68+dWgpGfRaePtXBei8HeWyfxzhbrCrJ2f0ktQ4O3otpJE75Q1GKGs+pt20GmDQa03zPA4ZVgvb0MeWdln4gtY0g14LYyzzbs0Xj0CaipFn9EnOTvK+JHcm+ViSl3TLH5HkhiSf7L6ePr5yJUlb1aejvx/4uar6YJKHAbcmuQF4HnBjVb02yeXA5Qz+YLj0VYYZrdjFL7BZdeu+S/gaIwd9VR0DjnWX/y3JncBZwB5gd7fa1Qz+aLhBvwBaDtW53bZ5D6X16ttq3ZPezq3uY5j37/uYjeXwyiS7gMcDtwCP6l4EHngxOGMczyFJGk3vnbFJvgn4Y+Bnq+pfkwx7v33APoCdO3f2LUObWJYjUGbeuc/70StL1slqoFfQJ3kwg5B/e1W9q1v8mSRnVtWxJGcCx9e6b1UdAA4ArKysVJ86tDXzGPrzWNPUzXsIz8OL2Lx/j+bUyEGfQet+JXBnVf3mqpsOAnuB13Zfr+9V4ZJYL+jW61DHFYYz74DXMI81bWgeAnAUi1r3VvjCAPTr6L8PeA7w0SQf7pb9IoOAvzbJZcDdwDP7lShJ6qPPUTd/A6w3kL9g1MfV1jn2GN3cvntYhm572pb4e+onY7VlfV5Y5jZYW7OII4tFrHlBGPRT1lr3Pel9CNqCVjvWaW7Xyc/VyAuOpymWpMbZ0WviHNfM2Cw74kV4rlbfCa1i0E9ISyOaUYLacFcvSxC+02TQn2RRAnqYIDVsJYEzeklqnh19T55qV9K8W9qg3+qIpqWRjjRWLc/TGzm239GNJDVuqTr6eet2560eaSpafgcwp5Yq6CfN4JYatsBjnCaDflHm6ZIW1HrvSvr8ucUJckYvSY1rsqPfKkcuksZiTvc/NBP0655FsUeIT+Ix+zyvJI3C0Y0kNc6gl6TGTSzok1yY5BNJjiS5fFLPI0na2ERm9EkeBLwReApwFPhAkoNVdccknk+SFsYMDrucVEf/BOBIVd1VVV8CrgH2TOi5JEkbmFTQnwXcs+r60W6ZJGnKJnV4ZdZYVl+1QrIP2Ndd/fcknxjxubYBn4VXj3j3hdRt81Jxm5dDm9v8V+svf/Wre23ztw2z0qSC/ihw9qrrO4B7V69QVQeAA32fKMnhqlrp+ziLxG1eDm7zcpjGNk9qdPMB4Nwk5yR5CHApcHBCzyVJ2sBEOvqquj/JTwPvBR4EXFVVH5vEc0mSNjaxUyBU1buBd0/q8VfpPf5ZQG7zcnCbl8PEtzlVtflakqSF5SkQJKlxCxP0m51SIclDk7yzu/2WJLumX+V4DbHNL0tyR5LbktyYZKhDrebZsKfOSHJJkkqy8EdoDLPNSX6k+1l/LMkfTrvGcRvid3tnkvcl+VD3+33RLOocpyRXJTme5PZ1bk+SN3Tfk9uSnDe2J6+quf/HYIfuPwDfDjwE+Ajw2JPWeSHw5u7ypcA7Z133FLb5B4BTu8svWIZt7tZ7GHATcDOwMuu6p/BzPhf4EHB6d/2MWdc9hW0+ALygu/xY4NOzrnsM2/0k4Dzg9nVuvwh4D4PPIZ0P3DKu516Ujn6YUyrsAa7uLl8HXJBkrQ9uLYpNt7mq3ldVX+yu3szg8wqLbNhTZ/wy8GvAf02zuAkZZpt/EnhjVX0eoKqOT7nGcRtmmwt4eHf5mznpcziLqKpuAj63wSp7gLfVwM3AaUnOHMdzL0rQD3NKha+sU1X3A/cBj5xKdZOx1dNIXMagG1hkm25zkscDZ1fVn02zsAka5uf8aODRSf42yc1JLpxadZMxzDbvB56d5CiDo/dePJ3SZmpip45ZlL8wtekpFYZcZ5EMvT1Jng2sAN8/0Yomb8NtTvJ1wOuB502roCkY5ud8CoPxzW4G79r+OsnjquoLE65tUobZ5mcBb62q30jyROAPum3+38mXNzMTy7BF6eg3PaXC6nWSnMLg7d5Gb5Pm3TDbTJInA68CLq6q/55SbZOy2TY/DHgccCjJpxnMMQ8u+A7ZYX+3r6+qL1fVp4BPMAj+RTXMNl8GXAtQVe8Hvp7BeXBaNtT/+VEsStAPc0qFg8De7vIlwF9Wt4djQW26zd0Y43cZhPyiz21hk22uqvuqaltV7aqqXQz2S1xcVYdnU+5YDPO7/acMdryTZBuDUc5dU61yvIbZ5ruBCwCSfCeDoD8x1Sqn7yDw3O7om/OB+6rq2DgeeCFGN7XOKRWS/BJwuKoOAlcyeHt3hEEnf+nsKu5vyG1+HfBNwB91+53vrqqLZ1Z0T0Nuc1OG3Ob3Ak9NcgfwP8AvVNW/zK7qfobc5p8D3pLkpQzGF89b8MaNJO9gMH7b1u17uAJ4MEBVvZnBvoiLgCPAF4Hnj+25F/x7J0naxKKMbiRJIzLoJalxBr0kNc6gl6TGGfSS1DiDXpIaZ9BLUuMMeklq3P8BiTRJBBviVZ8AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(results[y==0],100, color='red', alpha=0.5)\n", "plt.hist(results[y==1],100, color='blue', alpha=0.5)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.899745138065494\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8686391472820838\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8524062144751801\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8642317966816166\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8784158027596011\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8867914123961473\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8849441217557532\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.868153076979634\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8743168394480798\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/fast_data/drewe/software/envs/tf_gpu/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 0.8746538244736908\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "array([0.04848157, 0.05704057, 0.01465255, ..., 0.77040749, 0.05716322,\n", " 0.05729546])" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Logistic regression (scikit)\n", "cv = StratifiedKFold(n_splits=10)\n", "results = np.zeros_like(y, dtype=float)\n", "\n", "tprs = []\n", "aucs = []\n", "mean_fpr = np.linspace(0, 1, 100)\n", "\n", "i = 0\n", "for train, test in cv.split(X, y):\n", " keras.backend.clear_session()\n", " prbs=[]\n", " model = LogisticRegression(random_state=0)\n", " \n", " quant_trans = sklearn.preprocessing.QuantileTransformer(output_distribution='uniform').fit(X[train,:])\n", " #quantile_transform(X, axis=1, output_distribution='uniform', copy=True)\n", " model.fit(quant_trans.transform(X[train,:]), y[train])\n", " probas_ = model.predict_proba(quant_trans.transform(X[test,:]))[:, 1]\n", " results[test] = probas_\n", " \n", " # Compute ROC curve and area the curve\n", " fpr, tpr, thresholds = roc_curve(y[test], probas_[ :])\n", " print(' ' + str(auc(fpr, tpr)))\n", " tprs.append(interp(mean_fpr, fpr, tpr))\n", " tprs[-1][0] = 0.0\n", " roc_auc = auc(fpr, tpr)\n", " aucs.append(roc_auc)\n", " plt.plot(fpr, tpr, lw=1, alpha=0.3,\n", " label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n", "\n", " i += 1\n", "plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n", " label='Chance', alpha=.8)\n", "\n", "mean_tpr = np.mean(tprs, axis=0)\n", "mean_tpr[-1] = 1.0\n", "mean_auc = auc(mean_fpr, mean_tpr)\n", "std_auc = np.std(aucs)\n", "plt.plot(mean_fpr, mean_tpr, color='b',\n", " label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n", " lw=2, alpha=.8)\n", "\n", "std_tpr = np.std(tprs, axis=0)\n", "tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n", "tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n", "plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n", " label=r'$\\pm$ 1 std. dev.')\n", "\n", "plt.xlim([-0.05, 1.05])\n", "plt.ylim([-0.05, 1.05])\n", "plt.xlabel('False Positive Rate')\n", "plt.ylabel('True Positive Rate')\n", "plt.title('Receiver operating characteristic example')\n", "plt.legend(loc=\"lower right\")\n", "plt.show()\n", "results" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "df_results = pd.DataFrame(data={\"name\": names, 'pred': results})\n", "df_results.to_csv('/home/drewe/notebooks/genotox/pred.lr2.norm.v4.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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2YtDP0LQDUJs32E7jpDdYacvW+zkONZW0pL8ng15TNUmQzs0IfR29dsqTBFef8Jn1vPo0gnLaz+nxBoN+UWznq4FJDnj6CmUK1gurRRqVLkofTq2nsZ2DQd+wWQbxvI/KTzJvITPvJvl5zcPPdMgaGntFsDRBv10HCPtsa8jwnKT/jtDnWJ+wPd1Ier0Qm4fg1mCaDvqhzsmepc3Oafetc90d1CKN0HV6LYT2okwBzakmgn4eAlrbb6F2TgbU1vmz27Qmgn7cLEfEfYJlWqHUwlku0lyZZL5+zuf0mwv6zTL0tNQcHU/XnOwAlj7oF92sd1TuGLVl27VTmdZ2F2gnadBPoM9Uj8EoLZk53AEY9JtkcEtaNAb9Ogx0Sa0w6CVpUnM4LTOJF213AZKk6TLoJalxUwv6JBcleTjJoSRXT2s7kqTTm0rQJzkD+C3gbcD5jD5H9vxpbEuSdHrTOhj7JuBQVT0KkORzwKXAN6a0PUmab+seyN0z9U1Pa+rmHODbY7cPd22SpBmb1og+a7TVSSske4G93c3/neThLW5rB/CdLT52Udnn5WCfl8C/Tq8+/9VJVppW0B8Gzhu7fS7wxPgKVbUf2N93Q0kOVNVq3+dZJPZ5Odjn5TCLPk9r6uYPgd1JXpPkpcBlwB1T2pYk6TSmMqKvquNJrgJ+DzgDuKGqvj6NbUmSTm9ql0CoqjuBO6f1/GN6T/8sIPu8HOzzcph6n1NVG68lSVpYXgJBkhq3MEG/0SUVkrwsya3d/V9Jsmv2VQ5rgj7/iyTfSPJgkruTTHSq1Tyb9NIZSX42SSVZ+DM0Julzknd2v+uvJ/ntWdc4tAn+tncm+VKSr3V/3xdvR51DSXJDkqNJDq5zf5J8qvt5PJjkjYMWUFVz/8XogO4jwGuBlwL/Ezj/lHX+CfDpbvky4NbtrnsGff5J4Ee65Z9fhj53670CuBe4D1jd7rpn8HveDXwNeGV3+6ztrnsGfd4P/Hy3fD7w2HbX3bPPbwXeCBxc5/6Lgf/M6D1Ibwa+MuT2F2VE/8NLKlTV/wVOXFJh3KXATd3yfwIuTLLWG7cWxYZ9rqovVdVz3c37GL1fYZFN8nsG+Djwq8D/mWVxUzJJn98P/FZVfRegqo7OuMahTdLnAv5St/yXOeV9OIumqu4Fnj7NKpcCN9fIfcCZSc4eavuLEvSTXFLhh+tU1XHgGeBHZ1LddGz2MhJXMhoRLLIN+5zkDcB5VfW7syxsiib5Pb8OeF2S/5bkviQXzay66Zikz/uAn0tymNHZe/90NqVtm6leNmZRPmFqw0sqTLjOIpm4P0l+DlgF/s5UK5q+0/Y5yYuATwLvmVVBMzDJ7/nFjKZv9jB61fblJD9eVf9ryrVNyyR9vhy4saquTfK3gP/Q9fkH0y9vW0w1vxZlRL/hJRXG10nyYkYv9073UmneTdJnkvwU8EvAJVX1/RnVNi0b9fkVwI8D9yR5jNFc5h0LfkB20r/tL1bV/6uqPwYeZhT8i2qSPl8J3AZQVf8d+AuMroPTqon+37dqUYJ+kksq3AFc0S3/LPBfqzvKsaA27HM3jfHvGYX8os/bwgZ9rqpnqmpHVe2qql2MjktcUlUHtqfcQUzyt/0FRgfeSbKD0VTOozOtcliT9Plx4EKAJD/GKOiPzbTK2boDeHd39s2bgWeq6shQT74QUze1ziUVknwMOFBVdwDXM3p5d4jRSP6y7au4vwn7/GvAy4H/2B13fryqLtm2onuasM9NmbDPvwf8dJJvAM8D/7Kqntq+qvuZsM8fBj6T5J8zmsJ4zyIP3JLcwmjqbUd33OEa4CUAVfVpRschLgYOAc8B7x10+wv8s5MkTWBRpm4kSVtk0EtS4wx6SWqcQS9JjTPoJalxBr0kNc6gl6TGGfSS1Lj/Dwqr3Bx//wWXAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(results[y==0],100, color='red', alpha=0.5)\n", "plt.hist(results[y==1],100, color='blue', alpha=0.5)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">>\n", " 0.9149390653840042\n", ">>\n", " 0.9166228654549011\n", ">>\n", " 0.8925973914850445\n", ">>\n", " 0.8909884077151189\n", ">>\n", " 0.900546528441536\n", ">>\n", " 0.9140075484645737\n", ">>\n", " 0.9102731416807588\n", ">>\n", " 0.9001053844080092\n", ">>\n", " 0.910092395167022\n", ">>\n", " 0.918032987770507\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "array([0.11857681, 0.17034412, 0.19707971, ..., 0.56568894, 0.24659538,\n", " 0.23726879])" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv = StratifiedKFold(n_splits=10)\n", "results = np.zeros_like(y, dtype=float)\n", "\n", "tprs = []\n", "aucs = []\n", "mean_fpr = np.linspace(0, 1, 100)\n", "\n", "i = 0\n", "for train, test in cv.split(X, y):\n", " print('>>')\n", " keras.backend.clear_session()\n", " prbs=[]\n", " model = RandomForestClassifier(n_estimators=1000, random_state=0, max_leaf_nodes=200)\n", " # Fit the model\n", " quant_trans = sklearn.preprocessing.QuantileTransformer(output_distribution='uniform').fit(X[train,:])\n", " #quantile_transform(X, axis=1, output_distribution='uniform', copy=True)\n", " model.fit(quant_trans.transform(X[train,:]), y[train])\n", " probas_ = model.predict_proba(quant_trans.transform(X[test,:]))[:, 1]\n", " results[test] = probas_\n", "\n", " # Compute ROC curve and area the curve\n", " fpr, tpr, thresholds = roc_curve(y[test], probas_[ :])\n", " print(' ' + str(auc(fpr, tpr)))\n", " tprs.append(interp(mean_fpr, fpr, tpr))\n", " tprs[-1][0] = 0.0\n", " roc_auc = auc(fpr, tpr)\n", " aucs.append(roc_auc)\n", " plt.plot(fpr, tpr, lw=1, alpha=0.3,\n", " label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n", "\n", " i += 1\n", "plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n", " label='Chance', alpha=.8)\n", "\n", "mean_tpr = np.mean(tprs, axis=0)\n", "mean_tpr[-1] = 1.0\n", "mean_auc = auc(mean_fpr, mean_tpr)\n", "std_auc = np.std(aucs)\n", "plt.plot(mean_fpr, mean_tpr, color='b',\n", " label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n", " lw=2, alpha=.8)\n", "\n", "std_tpr = np.std(tprs, axis=0)\n", "tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n", "tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n", "plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n", " label=r'$\\pm$ 1 std. dev.')\n", "\n", "plt.xlim([-0.05, 1.05])\n", "plt.ylim([-0.05, 1.05])\n", "plt.xlabel('False Positive Rate')\n", "plt.ylabel('True Positive Rate')\n", "plt.title('Receiver operating characteristic example')\n", "plt.legend(loc=\"lower right\")\n", "plt.show()\n", "results" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "df_results = pd.DataFrame(data={\"name\": names, 'pred': results})\n", "df_results.to_csv('/home/drewe/notebooks/genotox/pred.rf.norm.v4.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(results[y==0],100, color='red', alpha=0.5)\n", "plt.hist(results[y==1],100, color='blue', alpha=0.5)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">>\n", " 0.9077088095441821\n", ">>\n", " 0.8960444449877153\n", ">>\n", " 0.8856971726827122\n", ">>\n", " 0.8795125358429527\n", ">>\n", " 0.884052643188001\n", ">>\n", " 0.9000104159007914\n", ">>\n", " 0.8931696198808912\n", ">>\n", " 0.8840587701884667\n", ">>\n", " 0.8873550964389874\n", ">>\n", " 0.898101855255741\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "array([0.06428357, 0.025881 , 0.09142417, ..., 0.59375565, 0.06154057,\n", " 0.09877931])" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv = StratifiedKFold(n_splits=10)\n", "results = np.zeros_like(y, dtype=float)\n", "\n", "tprs = []\n", "aucs = []\n", "mean_fpr = np.linspace(0, 1, 100)\n", "\n", "i = 0\n", "for train, test in cv.split(X, y):\n", " print('>>')\n", " keras.backend.clear_session()\n", " prbs=[]\n", " model = SVC(kernel='rbf', gamma='scale', probability=True)\n", " # Fit the model\n", " quant_trans = sklearn.preprocessing.QuantileTransformer(output_distribution='uniform').fit(X[train,:])\n", " #quantile_transform(X, axis=1, output_distribution='uniform', copy=True)\n", " model.fit(quant_trans.transform(X[train,:]), y[train])\n", " probas_ = model.predict_proba(quant_trans.transform(X[test,:]))[:, 1]\n", " results[test] = probas_\n", "\n", " # Compute ROC curve and area the curve\n", " fpr, tpr, thresholds = roc_curve(y[test], probas_[ :])\n", " print(' ' + str(auc(fpr, tpr)))\n", " tprs.append(interp(mean_fpr, fpr, tpr))\n", " tprs[-1][0] = 0.0\n", " roc_auc = auc(fpr, tpr)\n", " aucs.append(roc_auc)\n", " plt.plot(fpr, tpr, lw=1, alpha=0.3,\n", " label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n", "\n", " i += 1\n", "plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n", " label='Chance', alpha=.8)\n", "\n", "mean_tpr = np.mean(tprs, axis=0)\n", "mean_tpr[-1] = 1.0\n", "mean_auc = auc(mean_fpr, mean_tpr)\n", "std_auc = np.std(aucs)\n", "plt.plot(mean_fpr, mean_tpr, color='b',\n", " label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n", " lw=2, alpha=.8)\n", "\n", "std_tpr = np.std(tprs, axis=0)\n", "tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n", "tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n", "plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n", " label=r'$\\pm$ 1 std. dev.')\n", "\n", "plt.xlim([-0.05, 1.05])\n", "plt.ylim([-0.05, 1.05])\n", "plt.xlabel('False Positive Rate')\n", "plt.ylabel('True Positive Rate')\n", "plt.title('Receiver operating characteristic example')\n", "plt.legend(loc=\"lower right\")\n", "plt.show()\n", "results" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "df_results = pd.DataFrame(data={\"name\": names, 'pred': results})\n", "df_results.to_csv('/home/drewe/notebooks/genotox/pred.svm.norm.v4.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(results[y==0],100, color='red', alpha=0.5)\n", "plt.hist(results[y==1],100, color='blue', alpha=0.5)\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": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }