深度殘差網路+自適應引數化ReLU啟用函式（調參記錄6）
續上一篇：
深度殘差網路+自適應引數化ReLU啟用函式（調參記錄5）
https://blog.csdn.net/dangqing1988/article/details/105627351
本文繼續調整超引數，測試Adaptively Parametric ReLU（APReLU）啟用函式在Cifar10影像集上的效果。APReLU的基本原理如下圖所示：
首先，從之前的調參發現，當學習率從0.1降到0.01和從0.01降到0.001的時候，loss會有大幅的下降。之前學習率降到0.001就結束了，那麼如果學習率繼續往下降的話，是不是loss還會繼續下降呢？
其次，當採用APReLU啟用函式時，深度殘差網路的結構比較複雜，更難訓練，也許需要更多的迭代次數。
因此，這次測試將迭代次數恢復成1000個epoch，將1-300、301-600、601-900、901-1000個epoch的學習率分別設定成了0.1、0.01、0.001、0.0001。
同時，最後全域性均值池化之前，如果採用APReLU的話，似乎是不利於模型訓練的。這是因為APReLU裡面用到了sigmoid函式。因此，全域性均值池化之前的APReLU改成了普通的ReLU。（對於殘差模組裡面的APReLU，由於恆等路徑的存在，其所導致訓練難度的增加應該是可以容忍的）
Keras程式碼如下：
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 14 04:17:45 2020
Implemented using TensorFlow 1.10.0 and Keras 2.2.1
Minghang Zhao, Shisheng Zhong, Xuyun Fu, Baoping Tang, Shaojiang Dong, Michael Pecht,
Deep Residual Networks with Adaptively Parametric Rectifier Linear Units for Fault Diagnosis,
IEEE Transactions on Industrial Electronics, 2020, DOI: 10.1109/TIE.2020.2972458
@author: Minghang Zhao
"""
from __future__ import print_function
import keras
import numpy as np
from keras.datasets import cifar10
from keras.layers import Dense, Conv2D, BatchNormalization, Activation, Minimum
from keras.layers import AveragePooling2D, Input, GlobalAveragePooling2D, Concatenate, Reshape
from keras.regularizers import l2
from keras import backend as K
from keras.models import Model
from keras import optimizers
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import LearningRateScheduler
K.set_learning_phase(1)
# The data, split between train and test sets
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
# Noised data
x_train = x_train.astype('float32') / 255.
x_test = x_test.astype('float32') / 255.
x_test = x_test-np.mean(x_train)
x_train = x_train-np.mean(x_train)
print('x_train shape:', x_train.shape)
print(x_train.shape[0], 'train samples')
print(x_test.shape[0], 'test samples')
# convert class vectors to binary class matrices
y_train = keras.utils.to_categorical(y_train, 10)
y_test = keras.utils.to_categorical(y_test, 10)
# Schedule the learning rate, multiply 0.1 every 300 epoches
def scheduler(epoch):
if epoch % 300 == 0 and epoch != 0:
lr = K.get_value(model.optimizer.lr)
K.set_value(model.optimizer.lr, lr * 0.1)
print("lr changed to {}".format(lr * 0.1))
return K.get_value(model.optimizer.lr)
# An adaptively parametric rectifier linear unit (APReLU)
def aprelu(inputs):
# get the number of channels
channels = inputs.get_shape().as_list()[-1]
# get a zero feature map
zeros_input = keras.layers.subtract([inputs, inputs])
# get a feature map with only positive features
pos_input = Activation('relu')(inputs)
# get a feature map with only negative features
neg_input = Minimum()([inputs,zeros_input])
# define a network to obtain the scaling coefficients
scales_p = GlobalAveragePooling2D()(pos_input)
scales_n = GlobalAveragePooling2D()(neg_input)
scales = Concatenate()([scales_n, scales_p])
scales = Dense(channels, activation='linear', kernel_initializer='he_normal', kernel_regularizer=l2(1e-4))(scales)
scales = BatchNormalization()(scales)
scales = Activation('relu')(scales)
scales = Dense(channels, activation='linear', kernel_initializer='he_normal', kernel_regularizer=l2(1e-4))(scales)
scales = BatchNormalization()(scales)
scales = Activation('sigmoid')(scales)
scales = Reshape((1,1,channels))(scales)
# apply a paramtetric relu
neg_part = keras.layers.multiply([scales, neg_input])
return keras.layers.add([pos_input, neg_part])
# Residual Block
def residual_block(incoming, nb_blocks, out_channels, downsample=False,
downsample_strides=2):
residual = incoming
in_channels = incoming.get_shape().as_list()[-1]
for i in range(nb_blocks):
identity = residual
if not downsample:
downsample_strides = 1
residual = BatchNormalization()(residual)
residual = aprelu(residual)
residual = Conv2D(out_channels, 3, strides=(downsample_strides, downsample_strides),
padding='same', kernel_initializer='he_normal',
kernel_regularizer=l2(1e-4))(residual)
residual = BatchNormalization()(residual)
residual = aprelu(residual)
residual = Conv2D(out_channels, 3, padding='same', kernel_initializer='he_normal',
kernel_regularizer=l2(1e-4))(residual)
# Downsampling
if downsample_strides > 1:
identity = AveragePooling2D(pool_size=(1,1), strides=(2,2))(identity)
# Zero_padding to match channels
if in_channels != out_channels:
zeros_identity = keras.layers.subtract([identity, identity])
identity = keras.layers.concatenate([identity, zeros_identity])
in_channels = out_channels
residual = keras.layers.add([residual, identity])
return residual
# define and train a model
inputs = Input(shape=(32, 32, 3))
net = Conv2D(16, 3, padding='same', kernel_initializer='he_normal', kernel_regularizer=l2(1e-4))(inputs)
net = residual_block(net, 9, 16, downsample=False)
net = residual_block(net, 1, 32, downsample=True)
net = residual_block(net, 8, 32, downsample=False)
net = residual_block(net, 1, 64, downsample=True)
net = residual_block(net, 8, 64, downsample=False)
net = BatchNormalization()(net)
net = Activation('relu')(net)
net = GlobalAveragePooling2D()(net)
outputs = Dense(10, activation='softmax', kernel_initializer='he_normal', kernel_regularizer=l2(1e-4))(net)
model = Model(inputs=inputs, outputs=outputs)
sgd = optimizers.SGD(lr=0.1, decay=0., momentum=0.9, nesterov=True)
model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])
# data augmentation
datagen = ImageDataGenerator(
# randomly rotate images in the range (deg 0 to 180)
rotation_range=30,
# randomly flip images
horizontal_flip=True,
# randomly shift images horizontally
width_shift_range=0.125,
# randomly shift images vertically
height_shift_range=0.125)
reduce_lr = LearningRateScheduler(scheduler)
# fit the model on the batches generated by datagen.flow().
model.fit_generator(datagen.flow(x_train, y_train, batch_size=100),
validation_data=(x_test, y_test), epochs=1000,
verbose=1, callbacks=[reduce_lr], workers=4)
# get results
K.set_learning_phase(0)
DRSN_train_score = model.evaluate(x_train, y_train, batch_size=100, verbose=0)
print('Train loss:', DRSN_train_score[0])
print('Train accuracy:', DRSN_train_score[1])
DRSN_test_score = model.evaluate(x_test, y_test, batch_size=100, verbose=0)
print('Test loss:', DRSN_test_score[0])
print('Test accuracy:', DRSN_test_score[1])
實驗結果如下：
Using TensorFlow backend. x_train shape: (50000, 32, 32, 3) 50000 train samples 10000 test samples Epoch 1/1000 500/500 [==============================] - 90s 179ms/step - loss: 2.6847 - acc: 0.4191 - val_loss: 2.2382 - val_acc: 0.5544 Epoch 2/1000 500/500 [==============================] - 62s 125ms/step - loss: 2.1556 - acc: 0.5605 - val_loss: 1.8942 - val_acc: 0.6254 Epoch 3/1000 500/500 [==============================] - 63s 125ms/step - loss: 1.8590 - acc: 0.6206 - val_loss: 1.6930 - val_acc: 0.6629 Epoch 4/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.6407 - acc: 0.6615 - val_loss: 1.4932 - val_acc: 0.6958 Epoch 5/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.4706 - acc: 0.6923 - val_loss: 1.3326 - val_acc: 0.7317 Epoch 6/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.3352 - acc: 0.7167 - val_loss: 1.2327 - val_acc: 0.7465 Epoch 7/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.2271 - acc: 0.7365 - val_loss: 1.1326 - val_acc: 0.7583 Epoch 8/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.1426 - acc: 0.7512 - val_loss: 1.0737 - val_acc: 0.7718 Epoch 9/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.0724 - acc: 0.7643 - val_loss: 1.0268 - val_acc: 0.7720 Epoch 10/1000 500/500 [==============================] - 62s 125ms/step - loss: 1.0256 - acc: 0.7687 - val_loss: 0.9672 - val_acc: 0.7842 Epoch 11/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.9772 - acc: 0.7766 - val_loss: 0.9104 - val_acc: 0.8032 Epoch 12/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.9385 - acc: 0.7839 - val_loss: 0.8971 - val_acc: 0.8017 Epoch 13/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.9109 - acc: 0.7910 - val_loss: 0.8675 - val_acc: 0.8073 Epoch 14/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.8799 - acc: 0.7961 - val_loss: 0.8410 - val_acc: 0.8118 Epoch 15/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.8680 - acc: 0.7975 - val_loss: 0.8337 - val_acc: 0.8106 Epoch 16/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.8426 - acc: 0.8045 - val_loss: 0.7960 - val_acc: 0.8194 Epoch 17/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.8230 - acc: 0.8088 - val_loss: 0.8293 - val_acc: 0.8065 Epoch 18/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.8143 - acc: 0.8094 - val_loss: 0.7952 - val_acc: 0.8215 Epoch 19/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7971 - acc: 0.8148 - val_loss: 0.7876 - val_acc: 0.8169 Epoch 20/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7856 - acc: 0.8204 - val_loss: 0.7765 - val_acc: 0.8247 Epoch 21/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.7774 - acc: 0.8191 - val_loss: 0.7441 - val_acc: 0.8361 Epoch 22/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7718 - acc: 0.8247 - val_loss: 0.7552 - val_acc: 0.8325 Epoch 23/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7674 - acc: 0.8272 - val_loss: 0.7786 - val_acc: 0.8241 Epoch 24/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7582 - acc: 0.8271 - val_loss: 0.7566 - val_acc: 0.8282 Epoch 25/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7448 - acc: 0.8315 - val_loss: 0.7507 - val_acc: 0.8336 Epoch 26/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7459 - acc: 0.8336 - val_loss: 0.7725 - val_acc: 0.8217 Epoch 27/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7418 - acc: 0.8340 - val_loss: 0.7581 - val_acc: 0.8335 Epoch 28/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.7335 - acc: 0.8354 - val_loss: 0.7402 - val_acc: 0.8360 Epoch 29/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7332 - acc: 0.8372 - val_loss: 0.7429 - val_acc: 0.8394 Epoch 30/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7243 - acc: 0.8405 - val_loss: 0.7322 - val_acc: 0.8393 Epoch 31/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.7227 - acc: 0.8422 - val_loss: 0.7098 - val_acc: 0.8468 Epoch 32/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7189 - acc: 0.8392 - val_loss: 0.7359 - val_acc: 0.8396 Epoch 33/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7144 - acc: 0.8455 - val_loss: 0.7071 - val_acc: 0.8442 Epoch 34/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7111 - acc: 0.8460 - val_loss: 0.7401 - val_acc: 0.8404 Epoch 35/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7061 - acc: 0.8480 - val_loss: 0.7155 - val_acc: 0.8497 Epoch 36/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.7072 - acc: 0.8488 - val_loss: 0.7355 - val_acc: 0.8430 Epoch 37/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.7077 - acc: 0.8496 - val_loss: 0.7167 - val_acc: 0.8521 Epoch 38/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6971 - acc: 0.8518 - val_loss: 0.7595 - val_acc: 0.8315 Epoch 39/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6971 - acc: 0.8508 - val_loss: 0.7278 - val_acc: 0.8423 Epoch 40/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6923 - acc: 0.8553 - val_loss: 0.7252 - val_acc: 0.8452 Epoch 41/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6935 - acc: 0.8538 - val_loss: 0.7169 - val_acc: 0.8461 Epoch 42/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6902 - acc: 0.8560 - val_loss: 0.7214 - val_acc: 0.8500 Epoch 43/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6874 - acc: 0.8576 - val_loss: 0.7078 - val_acc: 0.8492 Epoch 44/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6869 - acc: 0.8585 - val_loss: 0.7122 - val_acc: 0.8526 Epoch 45/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6830 - acc: 0.8587 - val_loss: 0.7509 - val_acc: 0.8411 Epoch 46/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6867 - acc: 0.8583 - val_loss: 0.7015 - val_acc: 0.8555 Epoch 47/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6795 - acc: 0.8614 - val_loss: 0.7051 - val_acc: 0.8529 Epoch 48/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6790 - acc: 0.8597 - val_loss: 0.7037 - val_acc: 0.8524 Epoch 49/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6790 - acc: 0.8612 - val_loss: 0.7121 - val_acc: 0.8526 Epoch 50/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6713 - acc: 0.8638 - val_loss: 0.7031 - val_acc: 0.8556 Epoch 51/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6655 - acc: 0.8658 - val_loss: 0.6827 - val_acc: 0.8617 Epoch 52/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6725 - acc: 0.8649 - val_loss: 0.7000 - val_acc: 0.8566 Epoch 53/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6669 - acc: 0.8677 - val_loss: 0.7089 - val_acc: 0.8599 Epoch 54/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6654 - acc: 0.8652 - val_loss: 0.6769 - val_acc: 0.8662 Epoch 55/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6674 - acc: 0.8668 - val_loss: 0.7016 - val_acc: 0.8570 Epoch 56/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6670 - acc: 0.8670 - val_loss: 0.6838 - val_acc: 0.8647 Epoch 57/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6667 - acc: 0.8672 - val_loss: 0.7112 - val_acc: 0.8595 Epoch 58/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6629 - acc: 0.8688 - val_loss: 0.7012 - val_acc: 0.8587 Epoch 59/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6649 - acc: 0.8678 - val_loss: 0.6854 - val_acc: 0.8656 Epoch 60/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6592 - acc: 0.8699 - val_loss: 0.6989 - val_acc: 0.8614 Epoch 61/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6591 - acc: 0.8696 - val_loss: 0.6978 - val_acc: 0.8603 Epoch 62/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6589 - acc: 0.8711 - val_loss: 0.6866 - val_acc: 0.8626 Epoch 63/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6516 - acc: 0.8736 - val_loss: 0.6845 - val_acc: 0.8612 Epoch 64/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6520 - acc: 0.8743 - val_loss: 0.7003 - val_acc: 0.8597 Epoch 65/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6544 - acc: 0.8736 - val_loss: 0.6992 - val_acc: 0.8593 Epoch 66/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6529 - acc: 0.8735 - val_loss: 0.6723 - val_acc: 0.8708 Epoch 67/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6534 - acc: 0.8740 - val_loss: 0.6958 - val_acc: 0.8610 Epoch 68/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6468 - acc: 0.8737 - val_loss: 0.6829 - val_acc: 0.8640 Epoch 69/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6463 - acc: 0.8760 - val_loss: 0.7142 - val_acc: 0.8552 Epoch 70/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6461 - acc: 0.8764 - val_loss: 0.6814 - val_acc: 0.8661 Epoch 71/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6459 - acc: 0.8764 - val_loss: 0.6884 - val_acc: 0.8656 Epoch 72/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6430 - acc: 0.8768 - val_loss: 0.6644 - val_acc: 0.8760 Epoch 73/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6406 - acc: 0.8774 - val_loss: 0.6803 - val_acc: 0.8710 Epoch 74/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6395 - acc: 0.8781 - val_loss: 0.6845 - val_acc: 0.8665 Epoch 75/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6413 - acc: 0.8773 - val_loss: 0.7124 - val_acc: 0.8560 Epoch 76/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6383 - acc: 0.8804 - val_loss: 0.7164 - val_acc: 0.8554 Epoch 77/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6385 - acc: 0.8806 - val_loss: 0.6843 - val_acc: 0.8661 Epoch 78/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6349 - acc: 0.8830 - val_loss: 0.7035 - val_acc: 0.8599 Epoch 79/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6330 - acc: 0.8818 - val_loss: 0.6983 - val_acc: 0.8591 Epoch 80/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6348 - acc: 0.8810 - val_loss: 0.6886 - val_acc: 0.8626 Epoch 81/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6323 - acc: 0.8817 - val_loss: 0.6763 - val_acc: 0.8680 Epoch 82/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6320 - acc: 0.8825 - val_loss: 0.6560 - val_acc: 0.8758 Epoch 83/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6327 - acc: 0.8820 - val_loss: 0.6592 - val_acc: 0.8779 Epoch 84/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6296 - acc: 0.8813 - val_loss: 0.6822 - val_acc: 0.8690 Epoch 85/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6310 - acc: 0.8810 - val_loss: 0.6825 - val_acc: 0.8703 Epoch 86/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6331 - acc: 0.8832 - val_loss: 0.6891 - val_acc: 0.8665 Epoch 87/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6330 - acc: 0.8818 - val_loss: 0.6806 - val_acc: 0.8704 Epoch 88/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6274 - acc: 0.8841 - val_loss: 0.6832 - val_acc: 0.8681 Epoch 89/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6313 - acc: 0.8821 - val_loss: 0.6796 - val_acc: 0.8694 Epoch 90/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6258 - acc: 0.8854 - val_loss: 0.6600 - val_acc: 0.8772 Epoch 91/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6270 - acc: 0.8841 - val_loss: 0.6670 - val_acc: 0.8758 Epoch 92/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6281 - acc: 0.8824 - val_loss: 0.6881 - val_acc: 0.8710 Epoch 93/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6265 - acc: 0.8847 - val_loss: 0.6886 - val_acc: 0.8698 Epoch 94/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6214 - acc: 0.8871 - val_loss: 0.6896 - val_acc: 0.8640 Epoch 95/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6241 - acc: 0.8860 - val_loss: 0.6674 - val_acc: 0.8721 Epoch 96/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6252 - acc: 0.8844 - val_loss: 0.6571 - val_acc: 0.8791 Epoch 97/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6227 - acc: 0.8856 - val_loss: 0.6486 - val_acc: 0.8797 Epoch 98/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6178 - acc: 0.8866 - val_loss: 0.6849 - val_acc: 0.8717 Epoch 99/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6162 - acc: 0.8881 - val_loss: 0.6726 - val_acc: 0.8709 Epoch 100/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6209 - acc: 0.8861 - val_loss: 0.6682 - val_acc: 0.8732 Epoch 101/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6190 - acc: 0.8883 - val_loss: 0.6810 - val_acc: 0.8723 Epoch 102/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6181 - acc: 0.8872 - val_loss: 0.6678 - val_acc: 0.8745 Epoch 103/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.6163 - acc: 0.8883 - val_loss: 0.6870 - val_acc: 0.8704 Epoch 104/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6105 - acc: 0.8910 - val_loss: 0.6576 - val_acc: 0.8775 Epoch 105/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6120 - acc: 0.8902 - val_loss: 0.6571 - val_acc: 0.8800 Epoch 106/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6146 - acc: 0.8882 - val_loss: 0.6560 - val_acc: 0.8772 Epoch 107/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6186 - acc: 0.8870 - val_loss: 0.6773 - val_acc: 0.8720 Epoch 108/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6189 - acc: 0.8879 - val_loss: 0.6503 - val_acc: 0.8846 Epoch 109/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6110 - acc: 0.8896 - val_loss: 0.6625 - val_acc: 0.8782 Epoch 110/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6185 - acc: 0.8862 - val_loss: 0.6735 - val_acc: 0.8712 Epoch 111/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6101 - acc: 0.8900 - val_loss: 0.6510 - val_acc: 0.8809 Epoch 112/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6132 - acc: 0.8897 - val_loss: 0.6817 - val_acc: 0.8703 Epoch 113/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6049 - acc: 0.8941 - val_loss: 0.6524 - val_acc: 0.8776 Epoch 114/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6129 - acc: 0.8884 - val_loss: 0.6532 - val_acc: 0.8778 Epoch 115/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6077 - acc: 0.8906 - val_loss: 0.6650 - val_acc: 0.8771 Epoch 116/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6079 - acc: 0.8915 - val_loss: 0.6643 - val_acc: 0.8759 Epoch 117/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6102 - acc: 0.8903 - val_loss: 0.6661 - val_acc: 0.8757 Epoch 118/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6103 - acc: 0.8909 - val_loss: 0.6641 - val_acc: 0.8748 Epoch 119/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6081 - acc: 0.8908 - val_loss: 0.6744 - val_acc: 0.8718 Epoch 120/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6060 - acc: 0.8931 - val_loss: 0.6355 - val_acc: 0.8881 Epoch 121/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6063 - acc: 0.8925 - val_loss: 0.6630 - val_acc: 0.8768 Epoch 122/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6101 - acc: 0.8901 - val_loss: 0.6482 - val_acc: 0.8799 Epoch 123/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6037 - acc: 0.8923 - val_loss: 0.6467 - val_acc: 0.8786 Epoch 124/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6016 - acc: 0.8942 - val_loss: 0.6487 - val_acc: 0.8788 Epoch 125/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6089 - acc: 0.8915 - val_loss: 0.6812 - val_acc: 0.8683 Epoch 126/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6042 - acc: 0.8943 - val_loss: 0.6480 - val_acc: 0.8830 Epoch 127/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6008 - acc: 0.8938 - val_loss: 0.6765 - val_acc: 0.8762 Epoch 128/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6023 - acc: 0.8940 - val_loss: 0.6676 - val_acc: 0.8755 Epoch 129/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6046 - acc: 0.8925 - val_loss: 0.6589 - val_acc: 0.8750 Epoch 130/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6008 - acc: 0.8949 - val_loss: 0.6580 - val_acc: 0.8805 Epoch 131/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6008 - acc: 0.8947 - val_loss: 0.6546 - val_acc: 0.8825 Epoch 132/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6009 - acc: 0.8946 - val_loss: 0.6434 - val_acc: 0.8833 Epoch 133/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6019 - acc: 0.8937 - val_loss: 0.6498 - val_acc: 0.8828 Epoch 134/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5977 - acc: 0.8942 - val_loss: 0.6527 - val_acc: 0.8796 Epoch 135/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.6013 - acc: 0.8941 - val_loss: 0.6239 - val_acc: 0.8875 Epoch 136/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5946 - acc: 0.8964 - val_loss: 0.6379 - val_acc: 0.8843 Epoch 137/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5959 - acc: 0.8945 - val_loss: 0.6549 - val_acc: 0.8792 Epoch 138/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5975 - acc: 0.8946 - val_loss: 0.6546 - val_acc: 0.8814 Epoch 139/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5954 - acc: 0.8958 - val_loss: 0.6686 - val_acc: 0.8734 Epoch 140/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5963 - acc: 0.8959 - val_loss: 0.6363 - val_acc: 0.8845 Epoch 141/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5959 - acc: 0.8947 - val_loss: 0.6745 - val_acc: 0.8745 Epoch 142/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5988 - acc: 0.8934 - val_loss: 0.6512 - val_acc: 0.8818 Epoch 143/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5940 - acc: 0.8977 - val_loss: 0.6644 - val_acc: 0.8784 Epoch 144/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5928 - acc: 0.8974 - val_loss: 0.6601 - val_acc: 0.8758 Epoch 145/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.6008 - acc: 0.8951 - val_loss: 0.6376 - val_acc: 0.8871 Epoch 146/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5949 - acc: 0.8962 - val_loss: 0.6469 - val_acc: 0.8855 Epoch 147/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5922 - acc: 0.8969 - val_loss: 0.6538 - val_acc: 0.8787 Epoch 148/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5964 - acc: 0.8968 - val_loss: 0.6406 - val_acc: 0.8842 Epoch 149/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5937 - acc: 0.8974 - val_loss: 0.6441 - val_acc: 0.8832 Epoch 150/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5988 - acc: 0.8955 - val_loss: 0.6565 - val_acc: 0.8786 Epoch 151/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5906 - acc: 0.8978 - val_loss: 0.6429 - val_acc: 0.8822 Epoch 152/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5928 - acc: 0.8969 - val_loss: 0.6567 - val_acc: 0.8777 Epoch 153/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5906 - acc: 0.8974 - val_loss: 0.6490 - val_acc: 0.8854 Epoch 154/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5916 - acc: 0.8977 - val_loss: 0.6577 - val_acc: 0.8789 Epoch 155/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5898 - acc: 0.8990 - val_loss: 0.6776 - val_acc: 0.8713 Epoch 156/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5947 - acc: 0.8975 - val_loss: 0.6373 - val_acc: 0.8840 Epoch 157/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5936 - acc: 0.8966 - val_loss: 0.6297 - val_acc: 0.8873 Epoch 158/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5873 - acc: 0.8995 - val_loss: 0.6499 - val_acc: 0.8765 Epoch 159/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5845 - acc: 0.8995 - val_loss: 0.6369 - val_acc: 0.8839 Epoch 160/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5928 - acc: 0.8961 - val_loss: 0.6585 - val_acc: 0.8782 Epoch 161/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5877 - acc: 0.8970 - val_loss: 0.6343 - val_acc: 0.8836 Epoch 162/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5868 - acc: 0.9000 - val_loss: 0.6437 - val_acc: 0.8803 Epoch 163/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5902 - acc: 0.8980 - val_loss: 0.6356 - val_acc: 0.8863 Epoch 164/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5832 - acc: 0.9012 - val_loss: 0.6400 - val_acc: 0.8874 Epoch 165/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5892 - acc: 0.8984 - val_loss: 0.6582 - val_acc: 0.8766 Epoch 166/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5867 - acc: 0.9009 - val_loss: 0.6727 - val_acc: 0.8725 Epoch 167/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5857 - acc: 0.9007 - val_loss: 0.6682 - val_acc: 0.8746 Epoch 168/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5886 - acc: 0.8999 - val_loss: 0.6429 - val_acc: 0.8844 Epoch 169/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5855 - acc: 0.8996 - val_loss: 0.6534 - val_acc: 0.8780 Epoch 170/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5877 - acc: 0.8997 - val_loss: 0.6453 - val_acc: 0.8814 Epoch 171/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5852 - acc: 0.8978 - val_loss: 0.6388 - val_acc: 0.8846 Epoch 172/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5878 - acc: 0.8986 - val_loss: 0.6310 - val_acc: 0.8883 Epoch 173/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5862 - acc: 0.9018 - val_loss: 0.6279 - val_acc: 0.8885 Epoch 174/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5867 - acc: 0.8993 - val_loss: 0.6682 - val_acc: 0.8762 Epoch 175/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5859 - acc: 0.8995 - val_loss: 0.6573 - val_acc: 0.8798 Epoch 176/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5828 - acc: 0.9017 - val_loss: 0.6472 - val_acc: 0.8835 Epoch 177/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5819 - acc: 0.9010 - val_loss: 0.6735 - val_acc: 0.8753 Epoch 178/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5875 - acc: 0.8993 - val_loss: 0.6420 - val_acc: 0.8860 Epoch 179/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5840 - acc: 0.9000 - val_loss: 0.6490 - val_acc: 0.8809 Epoch 180/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5796 - acc: 0.9035 - val_loss: 0.6586 - val_acc: 0.8760 Epoch 181/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5811 - acc: 0.9031 - val_loss: 0.6387 - val_acc: 0.8864 Epoch 182/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5811 - acc: 0.9015 - val_loss: 0.6334 - val_acc: 0.8890 Epoch 183/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5835 - acc: 0.9017 - val_loss: 0.6471 - val_acc: 0.8775 Epoch 184/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5801 - acc: 0.9015 - val_loss: 0.6620 - val_acc: 0.8785 Epoch 185/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5770 - acc: 0.9023 - val_loss: 0.6412 - val_acc: 0.8842 Epoch 186/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5768 - acc: 0.9024 - val_loss: 0.6341 - val_acc: 0.8828 Epoch 187/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5817 - acc: 0.9006 - val_loss: 0.6304 - val_acc: 0.8896 Epoch 188/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5835 - acc: 0.9008 - val_loss: 0.6491 - val_acc: 0.8820 Epoch 189/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5863 - acc: 0.8995 - val_loss: 0.6389 - val_acc: 0.8825 Epoch 190/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5832 - acc: 0.9016 - val_loss: 0.6362 - val_acc: 0.8833 Epoch 191/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5798 - acc: 0.9022 - val_loss: 0.6460 - val_acc: 0.8804 Epoch 192/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5801 - acc: 0.9007 - val_loss: 0.6358 - val_acc: 0.8869 Epoch 193/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5807 - acc: 0.9016 - val_loss: 0.6472 - val_acc: 0.8820 Epoch 194/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5774 - acc: 0.9024 - val_loss: 0.6542 - val_acc: 0.8825 Epoch 195/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5758 - acc: 0.9034 - val_loss: 0.6429 - val_acc: 0.8832 Epoch 196/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5784 - acc: 0.9020 - val_loss: 0.6505 - val_acc: 0.8826 Epoch 197/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5830 - acc: 0.9010 - val_loss: 0.6669 - val_acc: 0.8741 Epoch 198/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5769 - acc: 0.9026 - val_loss: 0.6474 - val_acc: 0.8814 Epoch 199/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5772 - acc: 0.9031 - val_loss: 0.6297 - val_acc: 0.8862 Epoch 200/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5780 - acc: 0.9023 - val_loss: 0.6459 - val_acc: 0.8843 Epoch 201/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5816 - acc: 0.9016 - val_loss: 0.6652 - val_acc: 0.8745 Epoch 202/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5764 - acc: 0.9032 - val_loss: 0.6306 - val_acc: 0.8869 Epoch 203/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5759 - acc: 0.9038 - val_loss: 0.6328 - val_acc: 0.8881 Epoch 204/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.5766 - acc: 0.9031 - val_loss: 0.6786 - val_acc: 0.8753 Epoch 205/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5756 - acc: 0.9035 - val_loss: 0.6442 - val_acc: 0.8841 Epoch 206/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5788 - acc: 0.9020 - val_loss: 0.6505 - val_acc: 0.8813 Epoch 207/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5797 - acc: 0.9019 - val_loss: 0.6414 - val_acc: 0.8839 Epoch 208/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5755 - acc: 0.9050 - val_loss: 0.6436 - val_acc: 0.8870 Epoch 209/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5782 - acc: 0.9013 - val_loss: 0.6619 - val_acc: 0.8765 Epoch 210/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5786 - acc: 0.9009 - val_loss: 0.6482 - val_acc: 0.8798 Epoch 211/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5727 - acc: 0.9039 - val_loss: 0.6324 - val_acc: 0.8879 Epoch 212/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5801 - acc: 0.9024 - val_loss: 0.6353 - val_acc: 0.8846 Epoch 213/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5747 - acc: 0.9046 - val_loss: 0.6388 - val_acc: 0.8827 Epoch 214/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5728 - acc: 0.9043 - val_loss: 0.6470 - val_acc: 0.8822 Epoch 215/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5747 - acc: 0.9045 - val_loss: 0.6394 - val_acc: 0.8889 Epoch 216/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5734 - acc: 0.9041 - val_loss: 0.6465 - val_acc: 0.8853 Epoch 217/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5696 - acc: 0.9072 - val_loss: 0.6500 - val_acc: 0.8838 Epoch 218/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5727 - acc: 0.9055 - val_loss: 0.6214 - val_acc: 0.8929 Epoch 219/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5737 - acc: 0.9048 - val_loss: 0.6288 - val_acc: 0.8885 Epoch 220/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5734 - acc: 0.9039 - val_loss: 0.6399 - val_acc: 0.8863 Epoch 221/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5740 - acc: 0.9047 - val_loss: 0.6256 - val_acc: 0.8906 Epoch 222/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5714 - acc: 0.9054 - val_loss: 0.6390 - val_acc: 0.8812 Epoch 223/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5795 - acc: 0.9017 - val_loss: 0.6447 - val_acc: 0.8851 Epoch 224/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5687 - acc: 0.9062 - val_loss: 0.6262 - val_acc: 0.8902 Epoch 225/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5713 - acc: 0.9034 - val_loss: 0.6379 - val_acc: 0.8857 Epoch 226/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5735 - acc: 0.9047 - val_loss: 0.6319 - val_acc: 0.8888 Epoch 227/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5749 - acc: 0.9044 - val_loss: 0.6353 - val_acc: 0.8870 Epoch 228/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5699 - acc: 0.9056 - val_loss: 0.6265 - val_acc: 0.8927 Epoch 229/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5718 - acc: 0.9048 - val_loss: 0.6291 - val_acc: 0.8865 Epoch 230/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5678 - acc: 0.9060 - val_loss: 0.6318 - val_acc: 0.8873 Epoch 231/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5699 - acc: 0.9060 - val_loss: 0.6378 - val_acc: 0.8859 Epoch 232/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5694 - acc: 0.9054 - val_loss: 0.6263 - val_acc: 0.8896 Epoch 233/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5748 - acc: 0.9040 - val_loss: 0.6202 - val_acc: 0.8964 Epoch 234/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5693 - acc: 0.9070 - val_loss: 0.6358 - val_acc: 0.8882 Epoch 235/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5712 - acc: 0.9040 - val_loss: 0.6529 - val_acc: 0.8811 Epoch 236/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5663 - acc: 0.9060 - val_loss: 0.6340 - val_acc: 0.8873 Epoch 237/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5717 - acc: 0.9047 - val_loss: 0.6391 - val_acc: 0.8869 Epoch 238/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5692 - acc: 0.9060 - val_loss: 0.6419 - val_acc: 0.8849 Epoch 239/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5732 - acc: 0.9059 - val_loss: 0.6274 - val_acc: 0.8862 Epoch 240/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5735 - acc: 0.9036 - val_loss: 0.6352 - val_acc: 0.8881 Epoch 241/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5672 - acc: 0.9064 - val_loss: 0.6263 - val_acc: 0.8871 Epoch 242/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5734 - acc: 0.9050 - val_loss: 0.6380 - val_acc: 0.8868 Epoch 243/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5693 - acc: 0.9061 - val_loss: 0.6313 - val_acc: 0.8865 Epoch 244/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5663 - acc: 0.9068 - val_loss: 0.6544 - val_acc: 0.8811 Epoch 245/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5697 - acc: 0.9066 - val_loss: 0.6647 - val_acc: 0.8791 Epoch 246/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5749 - acc: 0.9026 - val_loss: 0.6451 - val_acc: 0.8802 Epoch 247/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5712 - acc: 0.9053 - val_loss: 0.6448 - val_acc: 0.8837 Epoch 248/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5739 - acc: 0.9061 - val_loss: 0.6252 - val_acc: 0.8923 Epoch 249/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5716 - acc: 0.9051 - val_loss: 0.6571 - val_acc: 0.8809 Epoch 250/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5703 - acc: 0.9062 - val_loss: 0.6289 - val_acc: 0.8879 Epoch 251/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5689 - acc: 0.9055 - val_loss: 0.6302 - val_acc: 0.8898 Epoch 252/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5650 - acc: 0.9066 - val_loss: 0.6394 - val_acc: 0.8863 Epoch 253/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5688 - acc: 0.9067 - val_loss: 0.6249 - val_acc: 0.8884 Epoch 254/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5681 - acc: 0.9062 - val_loss: 0.6199 - val_acc: 0.8918 Epoch 255/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5661 - acc: 0.9079 - val_loss: 0.6540 - val_acc: 0.8822 Epoch 256/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5697 - acc: 0.9055 - val_loss: 0.6553 - val_acc: 0.8796 Epoch 257/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5672 - acc: 0.9067 - val_loss: 0.6183 - val_acc: 0.8944 Epoch 258/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5632 - acc: 0.9088 - val_loss: 0.6358 - val_acc: 0.8896 Epoch 259/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5679 - acc: 0.9063 - val_loss: 0.6347 - val_acc: 0.8866 Epoch 260/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5638 - acc: 0.9071 - val_loss: 0.6528 - val_acc: 0.8803 Epoch 261/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5723 - acc: 0.9055 - val_loss: 0.6438 - val_acc: 0.8848 Epoch 262/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5671 - acc: 0.9073 - val_loss: 0.6208 - val_acc: 0.8894 Epoch 263/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5677 - acc: 0.9057 - val_loss: 0.6412 - val_acc: 0.8846 Epoch 264/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5684 - acc: 0.9074 - val_loss: 0.6129 - val_acc: 0.8942 Epoch 265/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5701 - acc: 0.9072 - val_loss: 0.6283 - val_acc: 0.8881 Epoch 266/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5671 - acc: 0.9073 - val_loss: 0.6324 - val_acc: 0.8862 Epoch 267/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5630 - acc: 0.9078 - val_loss: 0.6319 - val_acc: 0.8862 Epoch 268/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5625 - acc: 0.9078 - val_loss: 0.6415 - val_acc: 0.8786 Epoch 269/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5605 - acc: 0.9084 - val_loss: 0.6366 - val_acc: 0.8871 Epoch 270/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5639 - acc: 0.9076 - val_loss: 0.6345 - val_acc: 0.8890 Epoch 271/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5692 - acc: 0.9052 - val_loss: 0.6379 - val_acc: 0.8817 Epoch 272/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5650 - acc: 0.9071 - val_loss: 0.6334 - val_acc: 0.8867 Epoch 273/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5651 - acc: 0.9082 - val_loss: 0.6315 - val_acc: 0.8869 Epoch 274/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5631 - acc: 0.9092 - val_loss: 0.6232 - val_acc: 0.8899 Epoch 275/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5642 - acc: 0.9086 - val_loss: 0.6296 - val_acc: 0.8907 Epoch 276/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5663 - acc: 0.9076 - val_loss: 0.6068 - val_acc: 0.8949 Epoch 277/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5685 - acc: 0.9057 - val_loss: 0.6036 - val_acc: 0.8994 Epoch 278/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5659 - acc: 0.9087 - val_loss: 0.6275 - val_acc: 0.8889 Epoch 279/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5677 - acc: 0.9065 - val_loss: 0.6267 - val_acc: 0.8872 Epoch 280/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5694 - acc: 0.9060 - val_loss: 0.6318 - val_acc: 0.8881 Epoch 281/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5601 - acc: 0.9100 - val_loss: 0.6203 - val_acc: 0.8932 Epoch 282/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5631 - acc: 0.9071 - val_loss: 0.6395 - val_acc: 0.8856 Epoch 283/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5646 - acc: 0.9088 - val_loss: 0.6373 - val_acc: 0.8895 Epoch 284/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5605 - acc: 0.9083 - val_loss: 0.6456 - val_acc: 0.8836 Epoch 285/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5618 - acc: 0.9094 - val_loss: 0.6225 - val_acc: 0.8900 Epoch 286/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5683 - acc: 0.9061 - val_loss: 0.6444 - val_acc: 0.8853 Epoch 287/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5661 - acc: 0.9075 - val_loss: 0.6479 - val_acc: 0.8834 Epoch 288/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5622 - acc: 0.9099 - val_loss: 0.6137 - val_acc: 0.8955 Epoch 289/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5630 - acc: 0.9075 - val_loss: 0.6212 - val_acc: 0.8944 Epoch 290/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5621 - acc: 0.9084 - val_loss: 0.6434 - val_acc: 0.8861 Epoch 291/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5656 - acc: 0.9087 - val_loss: 0.6248 - val_acc: 0.8911 Epoch 292/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5625 - acc: 0.9085 - val_loss: 0.6322 - val_acc: 0.8902 Epoch 293/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5637 - acc: 0.9094 - val_loss: 0.6321 - val_acc: 0.8867 Epoch 294/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5668 - acc: 0.9070 - val_loss: 0.6236 - val_acc: 0.8887 Epoch 295/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5622 - acc: 0.9091 - val_loss: 0.6359 - val_acc: 0.8880 Epoch 296/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5614 - acc: 0.9094 - val_loss: 0.6290 - val_acc: 0.8901 Epoch 297/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5610 - acc: 0.9092 - val_loss: 0.6358 - val_acc: 0.8905 Epoch 298/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5584 - acc: 0.9103 - val_loss: 0.6199 - val_acc: 0.8935 Epoch 299/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.5660 - acc: 0.9069 - val_loss: 0.6153 - val_acc: 0.8957 Epoch 300/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.5578 - acc: 0.9106 - val_loss: 0.6273 - val_acc: 0.8939 Epoch 301/1000 lr changed to 0.010000000149011612 500/500 [==============================] - 62s 124ms/step - loss: 0.4654 - acc: 0.9431 - val_loss: 0.5402 - val_acc: 0.9195 Epoch 302/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.4160 - acc: 0.9576 - val_loss: 0.5281 - val_acc: 0.9208 Epoch 303/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.3942 - acc: 0.9640 - val_loss: 0.5227 - val_acc: 0.9234 Epoch 304/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3791 - acc: 0.9677 - val_loss: 0.5185 - val_acc: 0.9257 Epoch 305/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3685 - acc: 0.9689 - val_loss: 0.5151 - val_acc: 0.9273 Epoch 306/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3548 - acc: 0.9717 - val_loss: 0.5098 - val_acc: 0.9268 Epoch 307/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3455 - acc: 0.9737 - val_loss: 0.5064 - val_acc: 0.9260 Epoch 308/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.3382 - acc: 0.9758 - val_loss: 0.5038 - val_acc: 0.9268 Epoch 309/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3281 - acc: 0.9766 - val_loss: 0.5063 - val_acc: 0.9248 Epoch 310/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3208 - acc: 0.9779 - val_loss: 0.5018 - val_acc: 0.9242 Epoch 311/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3133 - acc: 0.9792 - val_loss: 0.5024 - val_acc: 0.9248 Epoch 312/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.3078 - acc: 0.9790 - val_loss: 0.4962 - val_acc: 0.9250 Epoch 313/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.2999 - acc: 0.9810 - val_loss: 0.5008 - val_acc: 0.9234 Epoch 314/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2930 - acc: 0.9817 - val_loss: 0.4988 - val_acc: 0.9227 Epoch 315/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2868 - acc: 0.9824 - val_loss: 0.4896 - val_acc: 0.9221 Epoch 316/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2815 - acc: 0.9827 - val_loss: 0.4896 - val_acc: 0.9255 Epoch 317/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2752 - acc: 0.9834 - val_loss: 0.4882 - val_acc: 0.9233 Epoch 318/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2719 - acc: 0.9836 - val_loss: 0.4935 - val_acc: 0.9225 Epoch 319/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2659 - acc: 0.9839 - val_loss: 0.4843 - val_acc: 0.9230 Epoch 320/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2607 - acc: 0.9845 - val_loss: 0.4881 - val_acc: 0.9221 Epoch 321/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2561 - acc: 0.9850 - val_loss: 0.4871 - val_acc: 0.9200 Epoch 322/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2543 - acc: 0.9846 - val_loss: 0.4793 - val_acc: 0.9227 Epoch 323/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2500 - acc: 0.9852 - val_loss: 0.4661 - val_acc: 0.9221 Epoch 324/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2459 - acc: 0.9851 - val_loss: 0.4621 - val_acc: 0.9260 Epoch 325/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2410 - acc: 0.9855 - val_loss: 0.4690 - val_acc: 0.9236 Epoch 326/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2352 - acc: 0.9866 - val_loss: 0.4689 - val_acc: 0.9227 Epoch 327/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2334 - acc: 0.9860 - val_loss: 0.4711 - val_acc: 0.9205 Epoch 328/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2296 - acc: 0.9863 - val_loss: 0.4718 - val_acc: 0.9231 Epoch 329/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2259 - acc: 0.9869 - val_loss: 0.4648 - val_acc: 0.9212 Epoch 330/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2211 - acc: 0.9875 - val_loss: 0.4697 - val_acc: 0.9229 Epoch 331/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2228 - acc: 0.9861 - val_loss: 0.4697 - val_acc: 0.9200 Epoch 332/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.2175 - acc: 0.9862 - val_loss: 0.4546 - val_acc: 0.9224 Epoch 333/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2143 - acc: 0.9872 - val_loss: 0.4580 - val_acc: 0.9229 Epoch 334/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.2107 - acc: 0.9878 - val_loss: 0.4492 - val_acc: 0.9197 Epoch 335/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2080 - acc: 0.9875 - val_loss: 0.4626 - val_acc: 0.9184 Epoch 336/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2066 - acc: 0.9870 - val_loss: 0.4614 - val_acc: 0.9180 Epoch 337/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2045 - acc: 0.9871 - val_loss: 0.4447 - val_acc: 0.9210 Epoch 338/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.2001 - acc: 0.9874 - val_loss: 0.4554 - val_acc: 0.9207 Epoch 339/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1991 - acc: 0.9877 - val_loss: 0.4527 - val_acc: 0.9206 Epoch 340/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1958 - acc: 0.9878 - val_loss: 0.4630 - val_acc: 0.9157 Epoch 341/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1957 - acc: 0.9868 - val_loss: 0.4447 - val_acc: 0.9225 Epoch 342/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1939 - acc: 0.9870 - val_loss: 0.4558 - val_acc: 0.9160 Epoch 343/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.1921 - acc: 0.9866 - val_loss: 0.4451 - val_acc: 0.9195 Epoch 344/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1929 - acc: 0.9860 - val_loss: 0.4431 - val_acc: 0.9213 Epoch 345/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1889 - acc: 0.9864 - val_loss: 0.4386 - val_acc: 0.9213 Epoch 346/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1865 - acc: 0.9869 - val_loss: 0.4504 - val_acc: 0.9167 Epoch 347/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1847 - acc: 0.9870 - val_loss: 0.4285 - val_acc: 0.9196 Epoch 348/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1836 - acc: 0.9865 - val_loss: 0.4252 - val_acc: 0.9220 Epoch 349/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1827 - acc: 0.9864 - val_loss: 0.4364 - val_acc: 0.9205 Epoch 350/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1800 - acc: 0.9870 - val_loss: 0.4379 - val_acc: 0.9214 Epoch 351/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1793 - acc: 0.9869 - val_loss: 0.4343 - val_acc: 0.9193 Epoch 352/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1768 - acc: 0.9873 - val_loss: 0.4342 - val_acc: 0.9216 Epoch 353/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1784 - acc: 0.9855 - val_loss: 0.4390 - val_acc: 0.9192 Epoch 354/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.1763 - acc: 0.9860 - val_loss: 0.4257 - val_acc: 0.9197 Epoch 355/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1724 - acc: 0.9867 - val_loss: 0.4276 - val_acc: 0.9191 Epoch 356/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1727 - acc: 0.9867 - val_loss: 0.4395 - val_acc: 0.9202 Epoch 357/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1710 - acc: 0.9860 - val_loss: 0.4386 - val_acc: 0.9174 Epoch 358/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1722 - acc: 0.9852 - val_loss: 0.4284 - val_acc: 0.9179 Epoch 359/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1691 - acc: 0.9870 - val_loss: 0.4245 - val_acc: 0.9213 Epoch 360/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1687 - acc: 0.9859 - val_loss: 0.4181 - val_acc: 0.9153 Epoch 361/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1684 - acc: 0.9861 - val_loss: 0.4114 - val_acc: 0.9186 Epoch 362/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1650 - acc: 0.9867 - val_loss: 0.4036 - val_acc: 0.9195 Epoch 363/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1690 - acc: 0.9853 - val_loss: 0.4161 - val_acc: 0.9183 Epoch 364/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1651 - acc: 0.9859 - val_loss: 0.4265 - val_acc: 0.9159 Epoch 365/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1666 - acc: 0.9853 - val_loss: 0.4090 - val_acc: 0.9208 Epoch 366/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1650 - acc: 0.9854 - val_loss: 0.4077 - val_acc: 0.9237 Epoch 367/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1656 - acc: 0.9850 - val_loss: 0.4051 - val_acc: 0.9215 Epoch 368/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1616 - acc: 0.9860 - val_loss: 0.4279 - val_acc: 0.9154 Epoch 369/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1657 - acc: 0.9844 - val_loss: 0.4328 - val_acc: 0.9136 Epoch 370/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1624 - acc: 0.9851 - val_loss: 0.4312 - val_acc: 0.9144 Epoch 371/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1648 - acc: 0.9842 - val_loss: 0.4086 - val_acc: 0.9181 Epoch 372/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1615 - acc: 0.9853 - val_loss: 0.4178 - val_acc: 0.9195 Epoch 373/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1620 - acc: 0.9846 - val_loss: 0.3955 - val_acc: 0.9195 Epoch 374/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1602 - acc: 0.9853 - val_loss: 0.4074 - val_acc: 0.9197 Epoch 375/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1612 - acc: 0.9842 - val_loss: 0.4081 - val_acc: 0.9187 Epoch 376/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1611 - acc: 0.9845 - val_loss: 0.4138 - val_acc: 0.9174 Epoch 377/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1603 - acc: 0.9840 - val_loss: 0.4135 - val_acc: 0.9168 Epoch 378/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1597 - acc: 0.9840 - val_loss: 0.4254 - val_acc: 0.9158 Epoch 379/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1610 - acc: 0.9845 - val_loss: 0.4306 - val_acc: 0.9155 Epoch 380/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1590 - acc: 0.9842 - val_loss: 0.4183 - val_acc: 0.9137 Epoch 381/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1600 - acc: 0.9835 - val_loss: 0.4124 - val_acc: 0.9180 Epoch 382/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1574 - acc: 0.9840 - val_loss: 0.4224 - val_acc: 0.9173 Epoch 383/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1564 - acc: 0.9850 - val_loss: 0.4164 - val_acc: 0.9182 Epoch 384/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1535 - acc: 0.9855 - val_loss: 0.4009 - val_acc: 0.9218 Epoch 385/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1577 - acc: 0.9830 - val_loss: 0.4206 - val_acc: 0.9150 Epoch 386/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1576 - acc: 0.9838 - val_loss: 0.4181 - val_acc: 0.9158 Epoch 387/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1567 - acc: 0.9843 - val_loss: 0.4205 - val_acc: 0.9139 Epoch 388/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1548 - acc: 0.9845 - val_loss: 0.4168 - val_acc: 0.9160 Epoch 389/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1570 - acc: 0.9832 - val_loss: 0.4166 - val_acc: 0.9178 Epoch 390/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1557 - acc: 0.9842 - val_loss: 0.4142 - val_acc: 0.9159 Epoch 391/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1592 - acc: 0.9826 - val_loss: 0.4110 - val_acc: 0.9186 Epoch 392/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1577 - acc: 0.9832 - val_loss: 0.4116 - val_acc: 0.9180 Epoch 393/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1570 - acc: 0.9838 - val_loss: 0.4033 - val_acc: 0.9168 Epoch 394/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1564 - acc: 0.9838 - val_loss: 0.4234 - val_acc: 0.9134 Epoch 395/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1587 - acc: 0.9825 - val_loss: 0.3980 - val_acc: 0.9216 Epoch 396/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1562 - acc: 0.9833 - val_loss: 0.4011 - val_acc: 0.9188 Epoch 397/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1553 - acc: 0.9838 - val_loss: 0.4025 - val_acc: 0.9161 Epoch 398/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1531 - acc: 0.9845 - val_loss: 0.3951 - val_acc: 0.9195 Epoch 399/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1521 - acc: 0.9848 - val_loss: 0.4025 - val_acc: 0.9188 Epoch 400/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1554 - acc: 0.9833 - val_loss: 0.4085 - val_acc: 0.9161 Epoch 401/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1542 - acc: 0.9841 - val_loss: 0.4103 - val_acc: 0.9202 Epoch 402/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1528 - acc: 0.9844 - val_loss: 0.4119 - val_acc: 0.9168 Epoch 403/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1566 - acc: 0.9825 - val_loss: 0.4014 - val_acc: 0.9186 Epoch 404/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1523 - acc: 0.9843 - val_loss: 0.4243 - val_acc: 0.9147 Epoch 405/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1520 - acc: 0.9850 - val_loss: 0.4182 - val_acc: 0.9159 Epoch 406/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1521 - acc: 0.9835 - val_loss: 0.4021 - val_acc: 0.9178 Epoch 407/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1566 - acc: 0.9823 - val_loss: 0.4143 - val_acc: 0.9150 Epoch 408/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1520 - acc: 0.9846 - val_loss: 0.3987 - val_acc: 0.9200 Epoch 409/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1538 - acc: 0.9837 - val_loss: 0.4051 - val_acc: 0.9160 Epoch 410/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1541 - acc: 0.9824 - val_loss: 0.4159 - val_acc: 0.9133 Epoch 411/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1540 - acc: 0.9834 - val_loss: 0.4171 - val_acc: 0.9119 Epoch 412/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1523 - acc: 0.9843 - val_loss: 0.4103 - val_acc: 0.9154 Epoch 413/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1502 - acc: 0.9845 - val_loss: 0.4164 - val_acc: 0.9148 Epoch 414/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1585 - acc: 0.9811 - val_loss: 0.4115 - val_acc: 0.9166 Epoch 415/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1508 - acc: 0.9844 - val_loss: 0.4210 - val_acc: 0.9119 Epoch 416/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1531 - acc: 0.9835 - val_loss: 0.4125 - val_acc: 0.9169 Epoch 417/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1502 - acc: 0.9838 - val_loss: 0.4174 - val_acc: 0.9139 Epoch 418/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1477 - acc: 0.9853 - val_loss: 0.4091 - val_acc: 0.9173 Epoch 419/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1529 - acc: 0.9831 - val_loss: 0.4144 - val_acc: 0.9151 Epoch 420/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1546 - acc: 0.9824 - val_loss: 0.3990 - val_acc: 0.9175 Epoch 421/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1502 - acc: 0.9843 - val_loss: 0.3900 - val_acc: 0.9187 Epoch 422/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1500 - acc: 0.9843 - val_loss: 0.4025 - val_acc: 0.9168 Epoch 423/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1551 - acc: 0.9824 - val_loss: 0.4141 - val_acc: 0.9173 Epoch 424/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1507 - acc: 0.9841 - val_loss: 0.4181 - val_acc: 0.9132 Epoch 425/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1517 - acc: 0.9835 - val_loss: 0.4149 - val_acc: 0.9178 Epoch 426/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1533 - acc: 0.9830 - val_loss: 0.4080 - val_acc: 0.9159 Epoch 427/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1500 - acc: 0.9840 - val_loss: 0.4227 - val_acc: 0.9111 Epoch 428/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1515 - acc: 0.9840 - val_loss: 0.4033 - val_acc: 0.9161 Epoch 429/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1487 - acc: 0.9846 - val_loss: 0.4152 - val_acc: 0.9151 Epoch 430/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1504 - acc: 0.9838 - val_loss: 0.4093 - val_acc: 0.9144 Epoch 431/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1479 - acc: 0.9849 - val_loss: 0.3920 - val_acc: 0.9185 Epoch 432/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1486 - acc: 0.9847 - val_loss: 0.4119 - val_acc: 0.9136 Epoch 433/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1518 - acc: 0.9839 - val_loss: 0.4071 - val_acc: 0.9161 Epoch 434/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1526 - acc: 0.9830 - val_loss: 0.4031 - val_acc: 0.9162 Epoch 435/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1519 - acc: 0.9835 - val_loss: 0.3861 - val_acc: 0.9210 Epoch 436/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1487 - acc: 0.9845 - val_loss: 0.4099 - val_acc: 0.9184 Epoch 437/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1531 - acc: 0.9823 - val_loss: 0.4020 - val_acc: 0.9205 Epoch 438/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1519 - acc: 0.9833 - val_loss: 0.4032 - val_acc: 0.9179 Epoch 439/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1523 - acc: 0.9832 - val_loss: 0.3972 - val_acc: 0.9171 Epoch 440/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1512 - acc: 0.9840 - val_loss: 0.3920 - val_acc: 0.9195 Epoch 441/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1503 - acc: 0.9835 - val_loss: 0.4231 - val_acc: 0.9130 Epoch 442/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1464 - acc: 0.9849 - val_loss: 0.4230 - val_acc: 0.9133 Epoch 443/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1509 - acc: 0.9837 - val_loss: 0.4154 - val_acc: 0.9127 Epoch 444/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1488 - acc: 0.9846 - val_loss: 0.4284 - val_acc: 0.9120 Epoch 445/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1468 - acc: 0.9853 - val_loss: 0.4246 - val_acc: 0.9143 Epoch 446/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1499 - acc: 0.9839 - val_loss: 0.4191 - val_acc: 0.9150 Epoch 447/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1494 - acc: 0.9841 - val_loss: 0.4146 - val_acc: 0.9183 Epoch 448/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1527 - acc: 0.9829 - val_loss: 0.4059 - val_acc: 0.9157 Epoch 449/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1491 - acc: 0.9845 - val_loss: 0.4126 - val_acc: 0.9151 Epoch 450/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1494 - acc: 0.9842 - val_loss: 0.4150 - val_acc: 0.9152 Epoch 451/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1521 - acc: 0.9838 - val_loss: 0.3997 - val_acc: 0.9176 Epoch 452/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1518 - acc: 0.9834 - val_loss: 0.4082 - val_acc: 0.9126 Epoch 453/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1514 - acc: 0.9835 - val_loss: 0.4053 - val_acc: 0.9177 Epoch 454/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1506 - acc: 0.9836 - val_loss: 0.4148 - val_acc: 0.9166 Epoch 455/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1493 - acc: 0.9845 - val_loss: 0.3997 - val_acc: 0.9207 Epoch 456/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1486 - acc: 0.9842 - val_loss: 0.4132 - val_acc: 0.9148 Epoch 457/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1479 - acc: 0.9856 - val_loss: 0.3984 - val_acc: 0.9181 Epoch 458/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1515 - acc: 0.9826 - val_loss: 0.4026 - val_acc: 0.9162 Epoch 459/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1515 - acc: 0.9838 - val_loss: 0.4098 - val_acc: 0.9137 Epoch 460/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1513 - acc: 0.9828 - val_loss: 0.4047 - val_acc: 0.9180 Epoch 461/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1466 - acc: 0.9855 - val_loss: 0.3965 - val_acc: 0.9193 Epoch 462/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1518 - acc: 0.9835 - val_loss: 0.4046 - val_acc: 0.9151 Epoch 463/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1506 - acc: 0.9839 - val_loss: 0.4084 - val_acc: 0.9140 Epoch 464/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1503 - acc: 0.9840 - val_loss: 0.4086 - val_acc: 0.9145 Epoch 465/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1523 - acc: 0.9837 - val_loss: 0.3983 - val_acc: 0.9184 Epoch 466/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1493 - acc: 0.9839 - val_loss: 0.3957 - val_acc: 0.9187 Epoch 467/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1492 - acc: 0.9840 - val_loss: 0.4008 - val_acc: 0.9212 Epoch 468/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1474 - acc: 0.9851 - val_loss: 0.4152 - val_acc: 0.9135 Epoch 469/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1466 - acc: 0.9851 - val_loss: 0.4033 - val_acc: 0.9179 Epoch 470/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1471 - acc: 0.9856 - val_loss: 0.3983 - val_acc: 0.9182 Epoch 471/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1473 - acc: 0.9846 - val_loss: 0.4316 - val_acc: 0.9089 Epoch 472/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1539 - acc: 0.9828 - val_loss: 0.3924 - val_acc: 0.9199 Epoch 473/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1483 - acc: 0.9847 - val_loss: 0.3929 - val_acc: 0.9197 Epoch 474/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1465 - acc: 0.9856 - val_loss: 0.4017 - val_acc: 0.9178 Epoch 475/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1541 - acc: 0.9831 - val_loss: 0.4030 - val_acc: 0.9145 Epoch 476/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1472 - acc: 0.9853 - val_loss: 0.4143 - val_acc: 0.9160 Epoch 477/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1498 - acc: 0.9842 - val_loss: 0.4277 - val_acc: 0.9121 Epoch 478/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1473 - acc: 0.9851 - val_loss: 0.4091 - val_acc: 0.9135 Epoch 479/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1513 - acc: 0.9838 - val_loss: 0.4148 - val_acc: 0.9163 Epoch 480/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1487 - acc: 0.9844 - val_loss: 0.4073 - val_acc: 0.9137 Epoch 481/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1446 - acc: 0.9862 - val_loss: 0.4056 - val_acc: 0.9184 Epoch 482/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1469 - acc: 0.9847 - val_loss: 0.4189 - val_acc: 0.9152 Epoch 483/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1447 - acc: 0.9855 - val_loss: 0.4097 - val_acc: 0.9169 Epoch 484/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1490 - acc: 0.9849 - val_loss: 0.3920 - val_acc: 0.9207 Epoch 485/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1466 - acc: 0.9853 - val_loss: 0.4131 - val_acc: 0.9162 Epoch 486/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1461 - acc: 0.9854 - val_loss: 0.4065 - val_acc: 0.9142 Epoch 487/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1479 - acc: 0.9849 - val_loss: 0.4088 - val_acc: 0.9159 Epoch 488/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1481 - acc: 0.9842 - val_loss: 0.4170 - val_acc: 0.9150 Epoch 489/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1480 - acc: 0.9843 - val_loss: 0.4196 - val_acc: 0.9114 Epoch 490/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1471 - acc: 0.9854 - val_loss: 0.4182 - val_acc: 0.9145 Epoch 491/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1457 - acc: 0.9859 - val_loss: 0.4128 - val_acc: 0.9173 Epoch 492/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1491 - acc: 0.9833 - val_loss: 0.4115 - val_acc: 0.9145 Epoch 493/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1483 - acc: 0.9845 - val_loss: 0.4246 - val_acc: 0.9138 Epoch 494/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1510 - acc: 0.9837 - val_loss: 0.4197 - val_acc: 0.9140 Epoch 495/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1441 - acc: 0.9863 - val_loss: 0.4147 - val_acc: 0.9143 Epoch 496/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1445 - acc: 0.9862 - val_loss: 0.4187 - val_acc: 0.9116 Epoch 497/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1469 - acc: 0.9854 - val_loss: 0.4090 - val_acc: 0.9181 Epoch 498/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1505 - acc: 0.9837 - val_loss: 0.3973 - val_acc: 0.9184 Epoch 499/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1479 - acc: 0.9847 - val_loss: 0.4087 - val_acc: 0.9166 Epoch 500/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1477 - acc: 0.9848 - val_loss: 0.4203 - val_acc: 0.9136 Epoch 501/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1492 - acc: 0.9845 - val_loss: 0.4222 - val_acc: 0.9131 Epoch 502/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1470 - acc: 0.9850 - val_loss: 0.4172 - val_acc: 0.9138 Epoch 503/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1497 - acc: 0.9839 - val_loss: 0.4288 - val_acc: 0.9133 Epoch 504/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1488 - acc: 0.9844 - val_loss: 0.4096 - val_acc: 0.9167 Epoch 505/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1467 - acc: 0.9854 - val_loss: 0.4186 - val_acc: 0.9139 Epoch 506/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1456 - acc: 0.9856 - val_loss: 0.4107 - val_acc: 0.9167 Epoch 507/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1488 - acc: 0.9847 - val_loss: 0.4200 - val_acc: 0.9152 Epoch 508/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1480 - acc: 0.9842 - val_loss: 0.4129 - val_acc: 0.9133 Epoch 509/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1497 - acc: 0.9838 - val_loss: 0.4048 - val_acc: 0.9136 Epoch 510/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1509 - acc: 0.9840 - val_loss: 0.3958 - val_acc: 0.9167 Epoch 511/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1478 - acc: 0.9850 - val_loss: 0.4136 - val_acc: 0.9157 Epoch 512/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1435 - acc: 0.9863 - val_loss: 0.4051 - val_acc: 0.9185 Epoch 513/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1458 - acc: 0.9856 - val_loss: 0.4088 - val_acc: 0.9154 Epoch 514/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1483 - acc: 0.9851 - val_loss: 0.4187 - val_acc: 0.9142 Epoch 515/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1463 - acc: 0.9853 - val_loss: 0.4347 - val_acc: 0.9096 Epoch 516/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1467 - acc: 0.9856 - val_loss: 0.4235 - val_acc: 0.9148 Epoch 517/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1452 - acc: 0.9854 - val_loss: 0.4250 - val_acc: 0.9135 Epoch 518/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1499 - acc: 0.9844 - val_loss: 0.4048 - val_acc: 0.9174 Epoch 519/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1482 - acc: 0.9843 - val_loss: 0.4159 - val_acc: 0.9140 Epoch 520/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1483 - acc: 0.9841 - val_loss: 0.4160 - val_acc: 0.9153 Epoch 521/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1464 - acc: 0.9858 - val_loss: 0.4009 - val_acc: 0.9165 Epoch 522/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1454 - acc: 0.9852 - val_loss: 0.4126 - val_acc: 0.9164 Epoch 523/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.1435 - acc: 0.9866 - val_loss: 0.4130 - val_acc: 0.9201 Epoch 524/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1478 - acc: 0.9848 - val_loss: 0.4095 - val_acc: 0.9172 Epoch 525/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1511 - acc: 0.9837 - val_loss: 0.4036 - val_acc: 0.9179 Epoch 526/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1491 - acc: 0.9842 - val_loss: 0.4036 - val_acc: 0.9173 Epoch 527/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1433 - acc: 0.9865 - val_loss: 0.4225 - val_acc: 0.9123 Epoch 528/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1453 - acc: 0.9854 - val_loss: 0.4156 - val_acc: 0.9156 Epoch 529/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1462 - acc: 0.9856 - val_loss: 0.4154 - val_acc: 0.9143 Epoch 530/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1500 - acc: 0.9840 - val_loss: 0.4176 - val_acc: 0.9120 Epoch 531/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1489 - acc: 0.9845 - val_loss: 0.4087 - val_acc: 0.9158 Epoch 532/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1480 - acc: 0.9849 - val_loss: 0.4042 - val_acc: 0.9154 Epoch 533/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1483 - acc: 0.9850 - val_loss: 0.4191 - val_acc: 0.9155 Epoch 534/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1432 - acc: 0.9865 - val_loss: 0.4054 - val_acc: 0.9173 Epoch 535/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1471 - acc: 0.9854 - val_loss: 0.4200 - val_acc: 0.9133 Epoch 536/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1518 - acc: 0.9835 - val_loss: 0.4052 - val_acc: 0.9160 Epoch 537/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1442 - acc: 0.9860 - val_loss: 0.4331 - val_acc: 0.9126 Epoch 538/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1466 - acc: 0.9848 - val_loss: 0.4207 - val_acc: 0.9173 Epoch 539/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1469 - acc: 0.9851 - val_loss: 0.4202 - val_acc: 0.9109 Epoch 540/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1496 - acc: 0.9838 - val_loss: 0.4297 - val_acc: 0.9126 Epoch 541/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1453 - acc: 0.9863 - val_loss: 0.4219 - val_acc: 0.9139 Epoch 542/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1469 - acc: 0.9854 - val_loss: 0.4203 - val_acc: 0.9137 Epoch 543/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1471 - acc: 0.9852 - val_loss: 0.4216 - val_acc: 0.9152 Epoch 544/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1514 - acc: 0.9840 - val_loss: 0.4178 - val_acc: 0.9138 Epoch 545/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1459 - acc: 0.9853 - val_loss: 0.4266 - val_acc: 0.9126 Epoch 546/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1480 - acc: 0.9845 - val_loss: 0.4147 - val_acc: 0.9176 Epoch 547/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1464 - acc: 0.9856 - val_loss: 0.4306 - val_acc: 0.9130 Epoch 548/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1490 - acc: 0.9840 - val_loss: 0.4259 - val_acc: 0.9143 Epoch 549/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1485 - acc: 0.9847 - val_loss: 0.4349 - val_acc: 0.9109 Epoch 550/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1487 - acc: 0.9844 - val_loss: 0.3984 - val_acc: 0.9189 Epoch 551/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1489 - acc: 0.9850 - val_loss: 0.4091 - val_acc: 0.9185 Epoch 552/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1486 - acc: 0.9845 - val_loss: 0.4143 - val_acc: 0.9138 Epoch 553/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1453 - acc: 0.9859 - val_loss: 0.4008 - val_acc: 0.9154 Epoch 554/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1445 - acc: 0.9864 - val_loss: 0.4308 - val_acc: 0.9134 Epoch 555/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1484 - acc: 0.9844 - val_loss: 0.4206 - val_acc: 0.9143 Epoch 556/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1455 - acc: 0.9856 - val_loss: 0.3994 - val_acc: 0.9197 Epoch 557/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1446 - acc: 0.9860 - val_loss: 0.3963 - val_acc: 0.9194 Epoch 558/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1460 - acc: 0.9852 - val_loss: 0.4125 - val_acc: 0.9140 Epoch 559/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1446 - acc: 0.9859 - val_loss: 0.4092 - val_acc: 0.9165 Epoch 560/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1442 - acc: 0.9865 - val_loss: 0.3911 - val_acc: 0.9212 Epoch 561/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1459 - acc: 0.9852 - val_loss: 0.3984 - val_acc: 0.9185 Epoch 562/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1473 - acc: 0.9851 - val_loss: 0.4080 - val_acc: 0.9196 Epoch 563/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1465 - acc: 0.9860 - val_loss: 0.4058 - val_acc: 0.9166 Epoch 564/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1423 - acc: 0.9870 - val_loss: 0.4046 - val_acc: 0.9180 Epoch 565/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1486 - acc: 0.9851 - val_loss: 0.4022 - val_acc: 0.9184 Epoch 566/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1478 - acc: 0.9853 - val_loss: 0.3896 - val_acc: 0.9224 Epoch 567/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1470 - acc: 0.9850 - val_loss: 0.4141 - val_acc: 0.9151 Epoch 568/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1438 - acc: 0.9862 - val_loss: 0.4139 - val_acc: 0.9197 Epoch 569/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1470 - acc: 0.9851 - val_loss: 0.4143 - val_acc: 0.9156 Epoch 570/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1484 - acc: 0.9845 - val_loss: 0.4151 - val_acc: 0.9148 Epoch 571/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1479 - acc: 0.9849 - val_loss: 0.4206 - val_acc: 0.9136 Epoch 572/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1458 - acc: 0.9855 - val_loss: 0.4172 - val_acc: 0.9147 Epoch 573/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1450 - acc: 0.9860 - val_loss: 0.4267 - val_acc: 0.9156 Epoch 574/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1514 - acc: 0.9834 - val_loss: 0.4357 - val_acc: 0.9127 Epoch 575/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1475 - acc: 0.9851 - val_loss: 0.4212 - val_acc: 0.9142 Epoch 576/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1464 - acc: 0.9858 - val_loss: 0.4141 - val_acc: 0.9162 Epoch 577/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1478 - acc: 0.9846 - val_loss: 0.4065 - val_acc: 0.9151 Epoch 578/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1418 - acc: 0.9868 - val_loss: 0.4090 - val_acc: 0.9145 Epoch 579/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1456 - acc: 0.9852 - val_loss: 0.4350 - val_acc: 0.9101 Epoch 580/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1422 - acc: 0.9870 - val_loss: 0.4116 - val_acc: 0.9185 Epoch 581/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1449 - acc: 0.9858 - val_loss: 0.4245 - val_acc: 0.9127 Epoch 582/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1429 - acc: 0.9863 - val_loss: 0.4157 - val_acc: 0.9163 Epoch 583/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1473 - acc: 0.9851 - val_loss: 0.4094 - val_acc: 0.9165 Epoch 584/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1500 - acc: 0.9845 - val_loss: 0.4269 - val_acc: 0.9115 Epoch 585/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1450 - acc: 0.9860 - val_loss: 0.4189 - val_acc: 0.9165 Epoch 586/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1450 - acc: 0.9859 - val_loss: 0.4153 - val_acc: 0.9153 Epoch 587/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1453 - acc: 0.9859 - val_loss: 0.4166 - val_acc: 0.9155 Epoch 588/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1409 - acc: 0.9875 - val_loss: 0.4088 - val_acc: 0.9193 Epoch 589/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1455 - acc: 0.9854 - val_loss: 0.4220 - val_acc: 0.9149 Epoch 590/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1466 - acc: 0.9848 - val_loss: 0.4264 - val_acc: 0.9136 Epoch 591/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1424 - acc: 0.9868 - val_loss: 0.4212 - val_acc: 0.9178 Epoch 592/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1441 - acc: 0.9862 - val_loss: 0.4271 - val_acc: 0.9127 Epoch 593/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1469 - acc: 0.9852 - val_loss: 0.4247 - val_acc: 0.9170 Epoch 594/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1468 - acc: 0.9845 - val_loss: 0.4080 - val_acc: 0.9192 Epoch 595/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1437 - acc: 0.9857 - val_loss: 0.4111 - val_acc: 0.9174 Epoch 596/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1451 - acc: 0.9852 - val_loss: 0.4290 - val_acc: 0.9124 Epoch 597/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1465 - acc: 0.9856 - val_loss: 0.4203 - val_acc: 0.9167 Epoch 598/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1451 - acc: 0.9855 - val_loss: 0.4203 - val_acc: 0.9136 Epoch 599/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1460 - acc: 0.9857 - val_loss: 0.4248 - val_acc: 0.9161 Epoch 600/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1466 - acc: 0.9856 - val_loss: 0.4286 - val_acc: 0.9143 Epoch 601/1000 lr changed to 0.0009999999776482583 500/500 [==============================] - 62s 125ms/step - loss: 0.1318 - acc: 0.9907 - val_loss: 0.3912 - val_acc: 0.9255 Epoch 602/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1212 - acc: 0.9945 - val_loss: 0.3822 - val_acc: 0.9269 Epoch 603/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1176 - acc: 0.9960 - val_loss: 0.3786 - val_acc: 0.9289 Epoch 604/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1168 - acc: 0.9959 - val_loss: 0.3779 - val_acc: 0.9286 Epoch 605/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1146 - acc: 0.9965 - val_loss: 0.3782 - val_acc: 0.9295 Epoch 606/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1130 - acc: 0.9973 - val_loss: 0.3791 - val_acc: 0.9294 Epoch 607/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1127 - acc: 0.9974 - val_loss: 0.3780 - val_acc: 0.9301 Epoch 608/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1118 - acc: 0.9976 - val_loss: 0.3777 - val_acc: 0.9300 Epoch 609/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1112 - acc: 0.9975 - val_loss: 0.3760 - val_acc: 0.9298 Epoch 610/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1102 - acc: 0.9978 - val_loss: 0.3769 - val_acc: 0.9301 Epoch 611/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1106 - acc: 0.9977 - val_loss: 0.3775 - val_acc: 0.9309 Epoch 612/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1092 - acc: 0.9979 - val_loss: 0.3781 - val_acc: 0.9304 Epoch 613/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1096 - acc: 0.9979 - val_loss: 0.3768 - val_acc: 0.9297 Epoch 614/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1092 - acc: 0.9979 - val_loss: 0.3770 - val_acc: 0.9302 Epoch 615/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1084 - acc: 0.9982 - val_loss: 0.3779 - val_acc: 0.9309 Epoch 616/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1077 - acc: 0.9983 - val_loss: 0.3804 - val_acc: 0.9299 Epoch 617/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1073 - acc: 0.9983 - val_loss: 0.3799 - val_acc: 0.9302 Epoch 618/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1069 - acc: 0.9985 - val_loss: 0.3816 - val_acc: 0.9305 Epoch 619/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1063 - acc: 0.9985 - val_loss: 0.3814 - val_acc: 0.9303 Epoch 620/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1066 - acc: 0.9983 - val_loss: 0.3817 - val_acc: 0.9301 Epoch 621/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1060 - acc: 0.9987 - val_loss: 0.3811 - val_acc: 0.9303 Epoch 622/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1058 - acc: 0.9985 - val_loss: 0.3815 - val_acc: 0.9298 Epoch 623/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1051 - acc: 0.9986 - val_loss: 0.3810 - val_acc: 0.9302 Epoch 624/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1050 - acc: 0.9986 - val_loss: 0.3825 - val_acc: 0.9303 Epoch 625/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1048 - acc: 0.9987 - val_loss: 0.3845 - val_acc: 0.9294 Epoch 626/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1040 - acc: 0.9988 - val_loss: 0.3842 - val_acc: 0.9296 Epoch 627/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1037 - acc: 0.9988 - val_loss: 0.3833 - val_acc: 0.9304 Epoch 628/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1048 - acc: 0.9982 - val_loss: 0.3844 - val_acc: 0.9303 Epoch 629/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1045 - acc: 0.9984 - val_loss: 0.3829 - val_acc: 0.9289 Epoch 630/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1032 - acc: 0.9988 - val_loss: 0.3823 - val_acc: 0.9302 Epoch 631/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1034 - acc: 0.9987 - val_loss: 0.3809 - val_acc: 0.9314 Epoch 632/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1029 - acc: 0.9987 - val_loss: 0.3812 - val_acc: 0.9309 Epoch 633/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1023 - acc: 0.9990 - val_loss: 0.3815 - val_acc: 0.9303 Epoch 634/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1025 - acc: 0.9987 - val_loss: 0.3854 - val_acc: 0.9303 Epoch 635/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1022 - acc: 0.9988 - val_loss: 0.3849 - val_acc: 0.9305 Epoch 636/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1015 - acc: 0.9989 - val_loss: 0.3840 - val_acc: 0.9312 Epoch 637/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1012 - acc: 0.9991 - val_loss: 0.3831 - val_acc: 0.9308 Epoch 638/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1012 - acc: 0.9990 - val_loss: 0.3830 - val_acc: 0.9315 Epoch 639/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1012 - acc: 0.9989 - val_loss: 0.3826 - val_acc: 0.9309 Epoch 640/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1006 - acc: 0.9990 - val_loss: 0.3838 - val_acc: 0.9309 Epoch 641/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.1004 - acc: 0.9989 - val_loss: 0.3843 - val_acc: 0.9315 Epoch 642/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0998 - acc: 0.9992 - val_loss: 0.3852 - val_acc: 0.9311 Epoch 643/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1001 - acc: 0.9991 - val_loss: 0.3846 - val_acc: 0.9309 Epoch 644/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.1000 - acc: 0.9990 - val_loss: 0.3847 - val_acc: 0.9304 Epoch 645/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0993 - acc: 0.9992 - val_loss: 0.3843 - val_acc: 0.9314 Epoch 646/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0993 - acc: 0.9991 - val_loss: 0.3823 - val_acc: 0.9313 Epoch 647/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0989 - acc: 0.9992 - val_loss: 0.3840 - val_acc: 0.9305 Epoch 648/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0991 - acc: 0.9990 - val_loss: 0.3843 - val_acc: 0.9313 Epoch 649/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0984 - acc: 0.9992 - val_loss: 0.3854 - val_acc: 0.9315 Epoch 650/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0982 - acc: 0.9991 - val_loss: 0.3853 - val_acc: 0.9322 Epoch 651/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0981 - acc: 0.9993 - val_loss: 0.3860 - val_acc: 0.9312 Epoch 652/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0982 - acc: 0.9990 - val_loss: 0.3880 - val_acc: 0.9307 Epoch 653/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0980 - acc: 0.9990 - val_loss: 0.3868 - val_acc: 0.9314 Epoch 654/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0973 - acc: 0.9993 - val_loss: 0.3846 - val_acc: 0.9319 Epoch 655/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0971 - acc: 0.9994 - val_loss: 0.3826 - val_acc: 0.9309 Epoch 656/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0970 - acc: 0.9990 - val_loss: 0.3831 - val_acc: 0.9319 Epoch 657/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0970 - acc: 0.9991 - val_loss: 0.3833 - val_acc: 0.9310 Epoch 658/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0966 - acc: 0.9992 - val_loss: 0.3810 - val_acc: 0.9314 Epoch 659/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0967 - acc: 0.9990 - val_loss: 0.3795 - val_acc: 0.9330 Epoch 660/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0962 - acc: 0.9992 - val_loss: 0.3816 - val_acc: 0.9329 Epoch 661/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0964 - acc: 0.9991 - val_loss: 0.3839 - val_acc: 0.9321 Epoch 662/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0956 - acc: 0.9992 - val_loss: 0.3841 - val_acc: 0.9321 Epoch 663/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0953 - acc: 0.9993 - val_loss: 0.3820 - val_acc: 0.9320 Epoch 664/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0949 - acc: 0.9994 - val_loss: 0.3808 - val_acc: 0.9326 Epoch 665/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.0957 - acc: 0.9990 - val_loss: 0.3808 - val_acc: 0.9332 Epoch 666/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0955 - acc: 0.9989 - val_loss: 0.3811 - val_acc: 0.9320 Epoch 667/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0948 - acc: 0.9993 - val_loss: 0.3811 - val_acc: 0.9330 Epoch 668/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0949 - acc: 0.9991 - val_loss: 0.3822 - val_acc: 0.9320 Epoch 669/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0947 - acc: 0.9992 - val_loss: 0.3843 - val_acc: 0.9321 Epoch 670/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0943 - acc: 0.9992 - val_loss: 0.3810 - val_acc: 0.9314 Epoch 671/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0941 - acc: 0.9991 - val_loss: 0.3823 - val_acc: 0.9324 Epoch 672/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0937 - acc: 0.9993 - val_loss: 0.3826 - val_acc: 0.9328 Epoch 673/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0936 - acc: 0.9992 - val_loss: 0.3816 - val_acc: 0.9330 Epoch 674/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0935 - acc: 0.9991 - val_loss: 0.3806 - val_acc: 0.9328 Epoch 675/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0931 - acc: 0.9992 - val_loss: 0.3828 - val_acc: 0.9331 Epoch 676/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0935 - acc: 0.9989 - val_loss: 0.3859 - val_acc: 0.9327 Epoch 677/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0927 - acc: 0.9993 - val_loss: 0.3836 - val_acc: 0.9329 Epoch 678/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0925 - acc: 0.9994 - val_loss: 0.3829 - val_acc: 0.9325 Epoch 679/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0924 - acc: 0.9993 - val_loss: 0.3823 - val_acc: 0.9341 Epoch 680/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0920 - acc: 0.9993 - val_loss: 0.3843 - val_acc: 0.9326 Epoch 681/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0922 - acc: 0.9993 - val_loss: 0.3855 - val_acc: 0.9315 Epoch 682/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0918 - acc: 0.9993 - val_loss: 0.3850 - val_acc: 0.9314 Epoch 683/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0915 - acc: 0.9994 - val_loss: 0.3850 - val_acc: 0.9312 Epoch 684/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0911 - acc: 0.9995 - val_loss: 0.3848 - val_acc: 0.9313 Epoch 685/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0908 - acc: 0.9996 - val_loss: 0.3854 - val_acc: 0.9322 Epoch 686/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0912 - acc: 0.9992 - val_loss: 0.3836 - val_acc: 0.9325 Epoch 687/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0909 - acc: 0.9993 - val_loss: 0.3848 - val_acc: 0.9320 Epoch 688/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.0904 - acc: 0.9995 - val_loss: 0.3857 - val_acc: 0.9316 Epoch 689/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0904 - acc: 0.9994 - val_loss: 0.3858 - val_acc: 0.9318 Epoch 690/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0901 - acc: 0.9995 - val_loss: 0.3829 - val_acc: 0.9320 Epoch 691/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0906 - acc: 0.9993 - val_loss: 0.3816 - val_acc: 0.9324 Epoch 692/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0900 - acc: 0.9992 - val_loss: 0.3827 - val_acc: 0.9308 Epoch 693/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0898 - acc: 0.9994 - val_loss: 0.3814 - val_acc: 0.9324 Epoch 694/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0898 - acc: 0.9994 - val_loss: 0.3820 - val_acc: 0.9329 Epoch 695/1000 500/500 [==============================] - 63s 125ms/step - loss: 0.0892 - acc: 0.9995 - val_loss: 0.3823 - val_acc: 0.9335 Epoch 696/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0893 - acc: 0.9992 - val_loss: 0.3825 - val_acc: 0.9326 Epoch 697/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0891 - acc: 0.9994 - val_loss: 0.3827 - val_acc: 0.9324 Epoch 698/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0892 - acc: 0.9992 - val_loss: 0.3812 - val_acc: 0.9331 Epoch 699/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0888 - acc: 0.9992 - val_loss: 0.3822 - val_acc: 0.9310 Epoch 700/1000 500/500 [==============================] - 62s 125ms/step - loss: 0.0883 - acc: 0.9995 - val_loss: 0.3825 - val_acc: 0.9317 Epoch 755/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0792 - acc: 0.9996 - val_loss: 0.3819 - val_acc: 0.9316 Epoch 756/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0791 - acc: 0.9996 - val_loss: 0.3808 - val_acc: 0.9312 Epoch 757/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0787 - acc: 0.9996 - val_loss: 0.3823 - val_acc: 0.9318 Epoch 758/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0788 - acc: 0.9995 - val_loss: 0.3813 - val_acc: 0.9322 Epoch 759/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0783 - acc: 0.9997 - val_loss: 0.3816 - val_acc: 0.9330 Epoch 760/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0782 - acc: 0.9997 - val_loss: 0.3780 - val_acc: 0.9331 Epoch 761/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0783 - acc: 0.9995 - val_loss: 0.3778 - val_acc: 0.9325 Epoch 762/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0780 - acc: 0.9996 - val_loss: 0.3769 - val_acc: 0.9319 Epoch 763/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0780 - acc: 0.9996 - val_loss: 0.3781 - val_acc: 0.9324 Epoch 764/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0779 - acc: 0.9996 - val_loss: 0.3798 - val_acc: 0.9331 Epoch 765/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0778 - acc: 0.9995 - val_loss: 0.3799 - val_acc: 0.9323 Epoch 766/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0777 - acc: 0.9996 - val_loss: 0.3809 - val_acc: 0.9311 Epoch 767/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0772 - acc: 0.9996 - val_loss: 0.3797 - val_acc: 0.9322 Epoch 768/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0772 - acc: 0.9996 - val_loss: 0.3814 - val_acc: 0.9323 Epoch 769/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0770 - acc: 0.9996 - val_loss: 0.3811 - val_acc: 0.9330 Epoch 770/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0763 - acc: 0.9999 - val_loss: 0.3816 - val_acc: 0.9331 Epoch 771/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0764 - acc: 0.9997 - val_loss: 0.3830 - val_acc: 0.9317 Epoch 772/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0767 - acc: 0.9995 - val_loss: 0.3810 - val_acc: 0.9320 Epoch 773/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0768 - acc: 0.9995 - val_loss: 0.3831 - val_acc: 0.9325 Epoch 774/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0764 - acc: 0.9995 - val_loss: 0.3824 - val_acc: 0.9334 Epoch 775/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0761 - acc: 0.9997 - val_loss: 0.3816 - val_acc: 0.9329 Epoch 776/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0758 - acc: 0.9997 - val_loss: 0.3815 - val_acc: 0.9340 Epoch 777/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0756 - acc: 0.9998 - val_loss: 0.3810 - val_acc: 0.9333 Epoch 778/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0756 - acc: 0.9996 - val_loss: 0.3838 - val_acc: 0.9322 Epoch 779/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0755 - acc: 0.9996 - val_loss: 0.3831 - val_acc: 0.9329 Epoch 780/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0756 - acc: 0.9994 - val_loss: 0.3833 - val_acc: 0.9313 Epoch 781/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0756 - acc: 0.9995 - val_loss: 0.3831 - val_acc: 0.9325 Epoch 782/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0751 - acc: 0.9996 - val_loss: 0.3820 - val_acc: 0.9340 Epoch 783/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0749 - acc: 0.9996 - val_loss: 0.3818 - val_acc: 0.9328 Epoch 784/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0749 - acc: 0.9995 - val_loss: 0.3788 - val_acc: 0.9331 Epoch 785/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0747 - acc: 0.9995 - val_loss: 0.3800 - val_acc: 0.9335 Epoch 786/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0745 - acc: 0.9996 - val_loss: 0.3790 - val_acc: 0.9333 Epoch 787/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0745 - acc: 0.9995 - val_loss: 0.3798 - val_acc: 0.9348 Epoch 788/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0746 - acc: 0.9995 - val_loss: 0.3808 - val_acc: 0.9340 Epoch 789/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0741 - acc: 0.9996 - val_loss: 0.3784 - val_acc: 0.9347 Epoch 790/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0741 - acc: 0.9996 - val_loss: 0.3764 - val_acc: 0.9334 Epoch 791/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0739 - acc: 0.9996 - val_loss: 0.3747 - val_acc: 0.9340 Epoch 792/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0736 - acc: 0.9996 - val_loss: 0.3762 - val_acc: 0.9326 Epoch 793/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0737 - acc: 0.9996 - val_loss: 0.3747 - val_acc: 0.9341 Epoch 794/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0736 - acc: 0.9996 - val_loss: 0.3778 - val_acc: 0.9322 Epoch 795/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0732 - acc: 0.9997 - val_loss: 0.3804 - val_acc: 0.9324 Epoch 796/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0732 - acc: 0.9996 - val_loss: 0.3771 - val_acc: 0.9336 Epoch 797/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0733 - acc: 0.9994 - val_loss: 0.3761 - val_acc: 0.9325 Epoch 798/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0729 - acc: 0.9996 - val_loss: 0.3770 - val_acc: 0.9323 Epoch 799/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0727 - acc: 0.9996 - val_loss: 0.3768 - val_acc: 0.9324 Epoch 800/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0725 - acc: 0.9997 - val_loss: 0.3784 - val_acc: 0.9329 Epoch 801/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0723 - acc: 0.9997 - val_loss: 0.3741 - val_acc: 0.9342 Epoch 802/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0723 - acc: 0.9996 - val_loss: 0.3772 - val_acc: 0.9332 Epoch 803/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0721 - acc: 0.9996 - val_loss: 0.3778 - val_acc: 0.9329 Epoch 804/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0722 - acc: 0.9995 - val_loss: 0.3759 - val_acc: 0.9337 Epoch 805/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0719 - acc: 0.9996 - val_loss: 0.3788 - val_acc: 0.9335 Epoch 806/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0719 - acc: 0.9995 - val_loss: 0.3815 - val_acc: 0.9332 Epoch 807/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0716 - acc: 0.9997 - val_loss: 0.3774 - val_acc: 0.9321 Epoch 808/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0714 - acc: 0.9997 - val_loss: 0.3774 - val_acc: 0.9337 Epoch 809/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0714 - acc: 0.9997 - val_loss: 0.3786 - val_acc: 0.9320 Epoch 810/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0713 - acc: 0.9996 - val_loss: 0.3776 - val_acc: 0.9322 Epoch 811/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0712 - acc: 0.9996 - val_loss: 0.3782 - val_acc: 0.9332 Epoch 812/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0709 - acc: 0.9997 - val_loss: 0.3837 - val_acc: 0.9322 Epoch 813/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0705 - acc: 0.9998 - val_loss: 0.3839 - val_acc: 0.9322 Epoch 814/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0707 - acc: 0.9996 - val_loss: 0.3820 - val_acc: 0.9318 Epoch 815/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0705 - acc: 0.9997 - val_loss: 0.3829 - val_acc: 0.9309 Epoch 816/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0703 - acc: 0.9996 - val_loss: 0.3810 - val_acc: 0.9318 Epoch 817/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0700 - acc: 0.9998 - val_loss: 0.3799 - val_acc: 0.9316 Epoch 818/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0701 - acc: 0.9996 - val_loss: 0.3789 - val_acc: 0.9314 Epoch 819/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0698 - acc: 0.9997 - val_loss: 0.3802 - val_acc: 0.9326 Epoch 820/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0699 - acc: 0.9996 - val_loss: 0.3837 - val_acc: 0.9301 Epoch 821/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0697 - acc: 0.9996 - val_loss: 0.3833 - val_acc: 0.9317 Epoch 822/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0698 - acc: 0.9995 - val_loss: 0.3851 - val_acc: 0.9305 Epoch 823/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0694 - acc: 0.9997 - val_loss: 0.3824 - val_acc: 0.9311 Epoch 824/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0693 - acc: 0.9995 - val_loss: 0.3830 - val_acc: 0.9303 Epoch 825/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0690 - acc: 0.9998 - val_loss: 0.3802 - val_acc: 0.9298 Epoch 826/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0689 - acc: 0.9996 - val_loss: 0.3810 - val_acc: 0.9305 Epoch 827/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0689 - acc: 0.9997 - val_loss: 0.3813 - val_acc: 0.9309 Epoch 828/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0688 - acc: 0.9996 - val_loss: 0.3799 - val_acc: 0.9316 Epoch 829/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0687 - acc: 0.9996 - val_loss: 0.3766 - val_acc: 0.9322 Epoch 830/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0688 - acc: 0.9995 - val_loss: 0.3764 - val_acc: 0.9329 Epoch 831/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0684 - acc: 0.9996 - val_loss: 0.3750 - val_acc: 0.9324 Epoch 832/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0685 - acc: 0.9996 - val_loss: 0.3781 - val_acc: 0.9314 Epoch 833/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0682 - acc: 0.9997 - val_loss: 0.3741 - val_acc: 0.9313 Epoch 834/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0682 - acc: 0.9996 - val_loss: 0.3738 - val_acc: 0.9312 Epoch 835/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0680 - acc: 0.9996 - val_loss: 0.3753 - val_acc: 0.9319 Epoch 836/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0679 - acc: 0.9997 - val_loss: 0.3753 - val_acc: 0.9317 Epoch 837/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0677 - acc: 0.9996 - val_loss: 0.3769 - val_acc: 0.9320 Epoch 838/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0674 - acc: 0.9997 - val_loss: 0.3775 - val_acc: 0.9317 Epoch 839/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0678 - acc: 0.9995 - val_loss: 0.3779 - val_acc: 0.9327 Epoch 840/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0673 - acc: 0.9995 - val_loss: 0.3773 - val_acc: 0.9319 Epoch 841/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0672 - acc: 0.9996 - val_loss: 0.3764 - val_acc: 0.9333 Epoch 842/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0670 - acc: 0.9997 - val_loss: 0.3741 - val_acc: 0.9323 Epoch 843/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0667 - acc: 0.9997 - val_loss: 0.3723 - val_acc: 0.9321 Epoch 844/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0667 - acc: 0.9997 - val_loss: 0.3731 - val_acc: 0.9315 Epoch 845/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0668 - acc: 0.9996 - val_loss: 0.3733 - val_acc: 0.9320 Epoch 846/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0666 - acc: 0.9996 - val_loss: 0.3722 - val_acc: 0.9315 Epoch 847/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0664 - acc: 0.9996 - val_loss: 0.3719 - val_acc: 0.9327 Epoch 848/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0662 - acc: 0.9997 - val_loss: 0.3720 - val_acc: 0.9309 Epoch 849/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0660 - acc: 0.9996 - val_loss: 0.3716 - val_acc: 0.9316 Epoch 850/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0660 - acc: 0.9996 - val_loss: 0.3732 - val_acc: 0.9310 Epoch 851/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0661 - acc: 0.9995 - val_loss: 0.3718 - val_acc: 0.9314 Epoch 852/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0657 - acc: 0.9997 - val_loss: 0.3748 - val_acc: 0.9300 Epoch 853/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0654 - acc: 0.9997 - val_loss: 0.3724 - val_acc: 0.9314 Epoch 854/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0658 - acc: 0.9995 - val_loss: 0.3750 - val_acc: 0.9283 Epoch 855/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0652 - acc: 0.9998 - val_loss: 0.3719 - val_acc: 0.9314 Epoch 856/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0652 - acc: 0.9998 - val_loss: 0.3724 - val_acc: 0.9314 Epoch 857/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0652 - acc: 0.9995 - val_loss: 0.3732 - val_acc: 0.9300 Epoch 858/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0648 - acc: 0.9997 - val_loss: 0.3714 - val_acc: 0.9307 Epoch 859/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0654 - acc: 0.9994 - val_loss: 0.3719 - val_acc: 0.9315 Epoch 860/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0645 - acc: 0.9997 - val_loss: 0.3726 - val_acc: 0.9308 Epoch 861/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0648 - acc: 0.9996 - val_loss: 0.3725 - val_acc: 0.9308 Epoch 862/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0645 - acc: 0.9997 - val_loss: 0.3698 - val_acc: 0.9312 Epoch 863/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0642 - acc: 0.9997 - val_loss: 0.3715 - val_acc: 0.9305 Epoch 864/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0643 - acc: 0.9997 - val_loss: 0.3724 - val_acc: 0.9302 Epoch 865/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0639 - acc: 0.9998 - val_loss: 0.3748 - val_acc: 0.9304 Epoch 866/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0641 - acc: 0.9995 - val_loss: 0.3751 - val_acc: 0.9315 Epoch 867/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0638 - acc: 0.9997 - val_loss: 0.3729 - val_acc: 0.9325 Epoch 868/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0637 - acc: 0.9997 - val_loss: 0.3750 - val_acc: 0.9320 Epoch 869/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0634 - acc: 0.9997 - val_loss: 0.3738 - val_acc: 0.9312 Epoch 870/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0634 - acc: 0.9996 - val_loss: 0.3731 - val_acc: 0.9313 Epoch 871/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0632 - acc: 0.9998 - val_loss: 0.3750 - val_acc: 0.9311 Epoch 872/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0633 - acc: 0.9997 - val_loss: 0.3784 - val_acc: 0.9313 Epoch 873/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0635 - acc: 0.9995 - val_loss: 0.3719 - val_acc: 0.9312 Epoch 874/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0631 - acc: 0.9996 - val_loss: 0.3706 - val_acc: 0.9330 Epoch 875/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0626 - acc: 0.9997 - val_loss: 0.3711 - val_acc: 0.9331 Epoch 876/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0628 - acc: 0.9996 - val_loss: 0.3730 - val_acc: 0.9332 Epoch 877/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0626 - acc: 0.9997 - val_loss: 0.3744 - val_acc: 0.9323 Epoch 878/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0623 - acc: 0.9997 - val_loss: 0.3724 - val_acc: 0.9321 Epoch 879/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0624 - acc: 0.9996 - val_loss: 0.3749 - val_acc: 0.9312 Epoch 880/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0621 - acc: 0.9997 - val_loss: 0.3728 - val_acc: 0.9314 Epoch 881/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0620 - acc: 0.9997 - val_loss: 0.3733 - val_acc: 0.9317 Epoch 882/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0623 - acc: 0.9996 - val_loss: 0.3779 - val_acc: 0.9298 Epoch 883/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0621 - acc: 0.9996 - val_loss: 0.3733 - val_acc: 0.9309 Epoch 884/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0617 - acc: 0.9997 - val_loss: 0.3714 - val_acc: 0.9312 Epoch 885/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0615 - acc: 0.9997 - val_loss: 0.3708 - val_acc: 0.9313 Epoch 886/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0615 - acc: 0.9997 - val_loss: 0.3727 - val_acc: 0.9305 Epoch 887/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0616 - acc: 0.9996 - val_loss: 0.3699 - val_acc: 0.9313 Epoch 888/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0611 - acc: 0.9997 - val_loss: 0.3709 - val_acc: 0.9310 Epoch 889/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0611 - acc: 0.9997 - val_loss: 0.3718 - val_acc: 0.9309 Epoch 890/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0611 - acc: 0.9997 - val_loss: 0.3721 - val_acc: 0.9315 Epoch 891/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0606 - acc: 0.9998 - val_loss: 0.3726 - val_acc: 0.9324 Epoch 892/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0606 - acc: 0.9997 - val_loss: 0.3737 - val_acc: 0.9321 Epoch 893/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0607 - acc: 0.9996 - val_loss: 0.3709 - val_acc: 0.9325 Epoch 894/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0602 - acc: 0.9999 - val_loss: 0.3701 - val_acc: 0.9325 Epoch 895/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0604 - acc: 0.9997 - val_loss: 0.3670 - val_acc: 0.9327 Epoch 896/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0606 - acc: 0.9995 - val_loss: 0.3646 - val_acc: 0.9325 Epoch 897/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0603 - acc: 0.9997 - val_loss: 0.3693 - val_acc: 0.9315 Epoch 898/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0602 - acc: 0.9996 - val_loss: 0.3705 - val_acc: 0.9312 Epoch 899/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0599 - acc: 0.9997 - val_loss: 0.3697 - val_acc: 0.9309 Epoch 900/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0600 - acc: 0.9997 - val_loss: 0.3694 - val_acc: 0.9313 Epoch 901/1000 lr changed to 9.999999310821295e-05 500/500 [==============================] - 62s 123ms/step - loss: 0.0597 - acc: 0.9998 - val_loss: 0.3694 - val_acc: 0.9313 Epoch 902/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0595 - acc: 0.9998 - val_loss: 0.3685 - val_acc: 0.9316 Epoch 903/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0597 - acc: 0.9998 - val_loss: 0.3685 - val_acc: 0.9314 Epoch 904/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0599 - acc: 0.9997 - val_loss: 0.3686 - val_acc: 0.9316 Epoch 905/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0598 - acc: 0.9997 - val_loss: 0.3684 - val_acc: 0.9316 Epoch 906/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0596 - acc: 0.9998 - val_loss: 0.3683 - val_acc: 0.9313 Epoch 907/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0596 - acc: 0.9998 - val_loss: 0.3681 - val_acc: 0.9314 Epoch 908/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3679 - val_acc: 0.9311 Epoch 909/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0597 - acc: 0.9997 - val_loss: 0.3676 - val_acc: 0.9309 Epoch 910/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0596 - acc: 0.9997 - val_loss: 0.3673 - val_acc: 0.9311 Epoch 911/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0597 - acc: 0.9997 - val_loss: 0.3675 - val_acc: 0.9311 Epoch 912/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0596 - acc: 0.9997 - val_loss: 0.3671 - val_acc: 0.9311 Epoch 913/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0595 - acc: 0.9997 - val_loss: 0.3666 - val_acc: 0.9314 Epoch 914/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3663 - val_acc: 0.9317 Epoch 915/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0598 - acc: 0.9996 - val_loss: 0.3660 - val_acc: 0.9318 Epoch 916/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0596 - acc: 0.9997 - val_loss: 0.3658 - val_acc: 0.9320 Epoch 917/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0595 - acc: 0.9997 - val_loss: 0.3658 - val_acc: 0.9318 Epoch 918/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0596 - acc: 0.9997 - val_loss: 0.3656 - val_acc: 0.9316 Epoch 919/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0595 - acc: 0.9997 - val_loss: 0.3654 - val_acc: 0.9316 Epoch 920/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0596 - acc: 0.9997 - val_loss: 0.3651 - val_acc: 0.9314 Epoch 921/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0593 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9314 Epoch 922/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9316 Epoch 923/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0593 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9316 Epoch 924/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3644 - val_acc: 0.9315 Epoch 925/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0592 - acc: 0.9998 - val_loss: 0.3648 - val_acc: 0.9315 Epoch 926/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0593 - acc: 0.9997 - val_loss: 0.3647 - val_acc: 0.9318 Epoch 927/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9313 Epoch 928/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9317 Epoch 929/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0592 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9320 Epoch 930/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9322 Epoch 931/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0592 - acc: 0.9999 - val_loss: 0.3647 - val_acc: 0.9318 Epoch 932/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0592 - acc: 0.9998 - val_loss: 0.3644 - val_acc: 0.9319 Epoch 933/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0594 - acc: 0.9997 - val_loss: 0.3642 - val_acc: 0.9319 Epoch 934/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0594 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9318 Epoch 935/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0594 - acc: 0.9997 - val_loss: 0.3641 - val_acc: 0.9318 Epoch 936/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0592 - acc: 0.9998 - val_loss: 0.3639 - val_acc: 0.9313 Epoch 937/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0592 - acc: 0.9998 - val_loss: 0.3637 - val_acc: 0.9321 Epoch 938/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9998 - val_loss: 0.3638 - val_acc: 0.9320 Epoch 939/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0590 - acc: 0.9999 - val_loss: 0.3638 - val_acc: 0.9320 Epoch 940/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9998 - val_loss: 0.3633 - val_acc: 0.9324 Epoch 941/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0591 - acc: 0.9998 - val_loss: 0.3635 - val_acc: 0.9325 Epoch 942/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0592 - acc: 0.9997 - val_loss: 0.3632 - val_acc: 0.9324 Epoch 943/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9997 - val_loss: 0.3637 - val_acc: 0.9330 Epoch 944/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9998 - val_loss: 0.3638 - val_acc: 0.9327 Epoch 945/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9997 - val_loss: 0.3641 - val_acc: 0.9329 Epoch 946/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9998 - val_loss: 0.3641 - val_acc: 0.9328 Epoch 947/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9997 - val_loss: 0.3645 - val_acc: 0.9328 Epoch 948/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0591 - acc: 0.9997 - val_loss: 0.3643 - val_acc: 0.9329 Epoch 949/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9997 - val_loss: 0.3643 - val_acc: 0.9328 Epoch 950/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9998 - val_loss: 0.3647 - val_acc: 0.9329 Epoch 951/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0589 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9330 Epoch 952/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9326 Epoch 953/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9997 - val_loss: 0.3645 - val_acc: 0.9326 Epoch 954/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0589 - acc: 0.9998 - val_loss: 0.3648 - val_acc: 0.9329 Epoch 955/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9999 - val_loss: 0.3648 - val_acc: 0.9327 Epoch 956/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3651 - val_acc: 0.9325 Epoch 957/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0589 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9324 Epoch 958/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9320 Epoch 959/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9322 Epoch 960/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9998 - val_loss: 0.3651 - val_acc: 0.9320 Epoch 961/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3652 - val_acc: 0.9325 Epoch 962/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9322 Epoch 963/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9997 - val_loss: 0.3649 - val_acc: 0.9324 Epoch 964/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9998 - val_loss: 0.3651 - val_acc: 0.9322 Epoch 965/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9324 Epoch 966/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0589 - acc: 0.9997 - val_loss: 0.3649 - val_acc: 0.9322 Epoch 967/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0590 - acc: 0.9996 - val_loss: 0.3649 - val_acc: 0.9328 Epoch 968/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9997 - val_loss: 0.3648 - val_acc: 0.9328 Epoch 969/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0589 - acc: 0.9998 - val_loss: 0.3647 - val_acc: 0.9325 Epoch 970/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9325 Epoch 971/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0587 - acc: 0.9997 - val_loss: 0.3646 - val_acc: 0.9328 Epoch 972/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9331 Epoch 973/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9331 Epoch 974/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9326 Epoch 975/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9322 Epoch 976/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0585 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9326 Epoch 977/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0591 - acc: 0.9996 - val_loss: 0.3646 - val_acc: 0.9323 Epoch 978/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9326 Epoch 979/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9997 - val_loss: 0.3646 - val_acc: 0.9320 Epoch 980/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9997 - val_loss: 0.3648 - val_acc: 0.9319 Epoch 981/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0587 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9317 Epoch 982/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0584 - acc: 0.9999 - val_loss: 0.3650 - val_acc: 0.9317 Epoch 983/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9323 Epoch 984/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9998 - val_loss: 0.3651 - val_acc: 0.9322 Epoch 985/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9997 - val_loss: 0.3651 - val_acc: 0.9321 Epoch 986/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0588 - acc: 0.9998 - val_loss: 0.3648 - val_acc: 0.9323 Epoch 987/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9997 - val_loss: 0.3644 - val_acc: 0.9318 Epoch 988/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9997 - val_loss: 0.3648 - val_acc: 0.9322 Epoch 989/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0585 - acc: 0.9998 - val_loss: 0.3650 - val_acc: 0.9322 Epoch 990/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9998 - val_loss: 0.3646 - val_acc: 0.9319 Epoch 991/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0584 - acc: 0.9998 - val_loss: 0.3647 - val_acc: 0.9323 Epoch 992/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0585 - acc: 0.9997 - val_loss: 0.3647 - val_acc: 0.9320 Epoch 993/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0587 - acc: 0.9997 - val_loss: 0.3646 - val_acc: 0.9318 Epoch 994/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0584 - acc: 0.9999 - val_loss: 0.3650 - val_acc: 0.9320 Epoch 995/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0586 - acc: 0.9997 - val_loss: 0.3650 - val_acc: 0.9315 Epoch 996/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0585 - acc: 0.9998 - val_loss: 0.3649 - val_acc: 0.9319 Epoch 997/1000 500/500 [==============================] - 62s 123ms/step - loss: 0.0585 - acc: 0.9998 - val_loss: 0.3645 - val_acc: 0.9318 Epoch 998/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0584 - acc: 0.9998 - val_loss: 0.3648 - val_acc: 0.9320 Epoch 999/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0584 - acc: 0.9999 - val_loss: 0.3646 - val_acc: 0.9320 Epoch 1000/1000 500/500 [==============================] - 62s 124ms/step - loss: 0.0581 - acc: 0.9999 - val_loss: 0.3646 - val_acc: 0.9323 Train loss: 0.062079589650034905 Train accuracy: 0.9986200013160705 Test loss: 0.3645842906832695 Test accuracy: 0.9323000019788742
中間有一部分epoch（從第701到754個epoch）的結果沒記錄下來。
Minghang Zhao, Shisheng Zhong, Xuyun Fu, Baoping Tang, Shaojiang Dong, Michael Pecht, Deep Residual Networks with Adaptively Parametric Rectifier Linear Units for Fault Diagnosis, IEEE Transactions on Industrial Electronics, 2020, DOI: 10.1109/TIE.2020.2972458
https://ieeexplore.ieee.org/document/8998530
————————————————
版權宣告：本文為CSDN博主「dangqing1988」的原創文章，遵循 CC 4.0 BY-SA 版權協議，轉載請附上原文出處連結及本宣告。
原文連結：https://blog.csdn.net/dangqing1988/article/details/105628681
來自 “ ITPUB部落格 ” ，連結：http://blog.itpub.net/69972329/viewspace-2687506/，如需轉載，請註明出處，否則將追究法律責任。
相關文章
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄1）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄2）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄3）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄4）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄5）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄7）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄8）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄9）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄10）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄11）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄12）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄13）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄14）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄15）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄16）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄17）函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄26）Cifar10~95.92%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄18）Cifar10~94.28%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄19）Cifar10~93.96%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄23）Cifar10~95.47%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄24）Cifar10~95.80%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄20）Cifar10~94.17%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄22）Cifar10~95.25%函式
- 深度殘差網路+自適應引數化ReLU啟用函式（調參記錄21）Cifar10~95.12%函式
- 注意力機制下的啟用函式：自適應引數化ReLU函式
- 深度殘差網路(ResNet)
- 深度學習之殘差網路深度學習
- 殘差網路再升級之深度殘差收縮網路（附Keras程式碼）Keras
- 深度殘差收縮網路：（三）網路結構
- 深度學習故障診斷——深度殘差收縮網路深度學習
- 深度殘差收縮網路：（一）背景知識
- 深度殘差收縮網路：（二）整體思路
- 十分鐘弄懂深度殘差收縮網路
- 深度殘差收縮網路：（五）實驗驗證
- 深度殘差收縮網路：（六）程式碼實現
- 從ReLU到GELU，一文概覽神經網路的啟用函式神經網路函式
- PHP函式，引數,可變參函式.PHP函式
- Excel函式應用教程：函式的引數(轉)Excel函式