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PIE_log.txt
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train log：
train:
(10262, 64, 64)
test:
(1292, 64, 64)
8209 train samples
2053 valid samples
1292 test samples
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_17 (Conv2D) (None, 64, 64, 32) 320
_________________________________________________________________
activation_25 (Activation) (None, 64, 64, 32) 0
_________________________________________________________________
conv2d_18 (Conv2D) (None, 62, 62, 32) 9248
_________________________________________________________________
activation_26 (Activation) (None, 62, 62, 32) 0
_________________________________________________________________
max_pooling2d_9 (MaxPooling2 (None, 31, 31, 32) 0
_________________________________________________________________
dropout_13 (Dropout) (None, 31, 31, 32) 0
_________________________________________________________________
conv2d_19 (Conv2D) (None, 31, 31, 64) 18496
_________________________________________________________________
activation_27 (Activation) (None, 31, 31, 64) 0
_________________________________________________________________
conv2d_20 (Conv2D) (None, 29, 29, 64) 36928
_________________________________________________________________
activation_28 (Activation) (None, 29, 29, 64) 0
_________________________________________________________________
max_pooling2d_10 (MaxPooling (None, 14, 14, 64) 0
_________________________________________________________________
dropout_14 (Dropout) (None, 14, 14, 64) 0
_________________________________________________________________
flatten_5 (Flatten) (None, 12544) 0
_________________________________________________________________
dense_9 (Dense) (None, 512) 6423040
_________________________________________________________________
activation_29 (Activation) (None, 512) 0
_________________________________________________________________
dropout_15 (Dropout) (None, 512) 0
_________________________________________________________________
dense_10 (Dense) (None, 68) 34884
_________________________________________________________________
activation_30 (Activation) (None, 68) 0
=================================================================
Total params: 6,522,916
Trainable params: 6,522,916
Non-trainable params: 0
_________________________________________________________________
Epoch 1/100
8209/8209 [==============================] - 23s - loss: 4.1946 - acc: 0.0206 - val_loss: 4.0815 - val_acc: 0.0502
Epoch 2/100
8209/8209 [==============================] - 22s - loss: 3.6200 - acc: 0.1363 - val_loss: 1.9657 - val_acc: 0.5153
Epoch 3/100
8209/8209 [==============================] - 22s - loss: 1.4879 - acc: 0.5981 - val_loss: 0.4984 - val_acc: 0.8914
Epoch 4/100
8209/8209 [==============================] - 23s - loss: 0.6589 - acc: 0.8198 - val_loss: 0.2226 - val_acc: 0.9498
Epoch 5/100
8209/8209 [==============================] - 23s - loss: 0.3889 - acc: 0.8899 - val_loss: 0.1776 - val_acc: 0.9630
Epoch 6/100
8209/8209 [==============================] - 23s - loss: 0.2809 - acc: 0.9190 - val_loss: 0.1541 - val_acc: 0.9625
Epoch 7/100
8209/8209 [==============================] - 23s - loss: 0.2090 - acc: 0.9352 - val_loss: 0.1001 - val_acc: 0.9727
Epoch 8/100
8209/8209 [==============================] - 23s - loss: 0.1662 - acc: 0.9498 - val_loss: 0.1183 - val_acc: 0.9703
Epoch 9/100
8209/8209 [==============================] - 23s - loss: 0.1471 - acc: 0.9582 - val_loss: 0.0913 - val_acc: 0.9776
Epoch 10/100
8209/8209 [==============================] - 23s - loss: 0.1163 - acc: 0.9648 - val_loss: 0.0752 - val_acc: 0.9805
Epoch 11/100
8209/8209 [==============================] - 23s - loss: 0.0989 - acc: 0.9719 - val_loss: 0.0743 - val_acc: 0.9825
Epoch 12/100
8209/8209 [==============================] - 23s - loss: 0.0920 - acc: 0.9711 - val_loss: 0.0874 - val_acc: 0.9844
Epoch 13/100
8209/8209 [==============================] - 23s - loss: 0.0765 - acc: 0.9771 - val_loss: 0.0840 - val_acc: 0.9810
Epoch 14/100
8209/8209 [==============================] - 23s - loss: 0.0686 - acc: 0.9786 - val_loss: 0.0705 - val_acc: 0.9849
Epoch 15/100
8209/8209 [==============================] - 23s - loss: 0.0699 - acc: 0.9771 - val_loss: 0.0860 - val_acc: 0.9805
Epoch 16/100
8209/8209 [==============================] - 23s - loss: 0.0685 - acc: 0.9800 - val_loss: 0.0759 - val_acc: 0.9820
Epoch 17/100
8209/8209 [==============================] - 23s - loss: 0.0466 - acc: 0.9853 - val_loss: 0.0689 - val_acc: 0.9859
Epoch 18/100
8209/8209 [==============================] - 23s - loss: 0.0402 - acc: 0.9878 - val_loss: 0.0668 - val_acc: 0.9854
Epoch 19/100
8209/8209 [==============================] - 23s - loss: 0.0466 - acc: 0.9859 - val_loss: 0.0793 - val_acc: 0.9815
Epoch 20/100
8209/8209 [==============================] - 23s - loss: 0.0384 - acc: 0.9879 - val_loss: 0.0792 - val_acc: 0.9844
Epoch 21/100
8209/8209 [==============================] - 23s - loss: 0.0391 - acc: 0.9878 - val_loss: 0.0611 - val_acc: 0.9859
Epoch 22/100
8209/8209 [==============================] - 23s - loss: 0.0465 - acc: 0.9875 - val_loss: 0.0576 - val_acc: 0.9854
Epoch 23/100
8209/8209 [==============================] - 23s - loss: 0.0233 - acc: 0.9921 - val_loss: 0.0561 - val_acc: 0.9864
Epoch 24/100
8209/8209 [==============================] - 23s - loss: 0.0299 - acc: 0.9910 - val_loss: 0.0686 - val_acc: 0.9873
Epoch 25/100
8209/8209 [==============================] - 23s - loss: 0.0271 - acc: 0.9922 - val_loss: 0.0550 - val_acc: 0.9888
Epoch 26/100
8209/8209 [==============================] - 23s - loss: 0.0250 - acc: 0.9915 - val_loss: 0.0667 - val_acc: 0.9907
Epoch 27/100
8209/8209 [==============================] - 23s - loss: 0.0421 - acc: 0.9862 - val_loss: 0.0571 - val_acc: 0.9878
Epoch 28/100
8209/8209 [==============================] - 23s - loss: 0.0298 - acc: 0.9914 - val_loss: 0.0664 - val_acc: 0.9849
Epoch 29/100
8209/8209 [==============================] - 23s - loss: 0.0309 - acc: 0.9903 - val_loss: 0.0578 - val_acc: 0.9903
Epoch 30/100
8209/8209 [==============================] - 23s - loss: 0.0255 - acc: 0.9921 - val_loss: 0.0560 - val_acc: 0.9878
Epoch 31/100
8209/8209 [==============================] - 23s - loss: 0.0196 - acc: 0.9944 - val_loss: 0.0661 - val_acc: 0.9873
Epoch 32/100
8209/8209 [==============================] - 23s - loss: 0.0160 - acc: 0.9945 - val_loss: 0.0735 - val_acc: 0.9878
Epoch 33/100
8209/8209 [==============================] - 23s - loss: 0.0128 - acc: 0.9954 - val_loss: 0.0635 - val_acc: 0.9883
Epoch 34/100
8209/8209 [==============================] - 23s - loss: 0.0204 - acc: 0.9931 - val_loss: 0.0590 - val_acc: 0.9878
Epoch 35/100
8209/8209 [==============================] - 23s - loss: 0.0208 - acc: 0.9943 - val_loss: 0.0638 - val_acc: 0.9873
Epoch 36/100
8209/8209 [==============================] - 23s - loss: 0.0226 - acc: 0.9937 - val_loss: 0.0597 - val_acc: 0.9849
Epoch 37/100
8209/8209 [==============================] - 23s - loss: 0.0201 - acc: 0.9934 - val_loss: 0.0623 - val_acc: 0.9864
Epoch 38/100
8209/8209 [==============================] - 23s - loss: 0.0196 - acc: 0.9945 - val_loss: 0.0633 - val_acc: 0.9878
Epoch 39/100
8209/8209 [==============================] - 23s - loss: 0.0218 - acc: 0.9926 - val_loss: 0.0554 - val_acc: 0.9888
Epoch 40/100
8209/8209 [==============================] - 23s - loss: 0.0195 - acc: 0.9926 - val_loss: 0.0567 - val_acc: 0.9903
Epoch 41/100
8209/8209 [==============================] - 23s - loss: 0.0165 - acc: 0.9954 - val_loss: 0.0586 - val_acc: 0.9883
Epoch 42/100
8209/8209 [==============================] - 23s - loss: 0.0153 - acc: 0.9952 - val_loss: 0.0641 - val_acc: 0.9898
Epoch 43/100
8209/8209 [==============================] - 23s - loss: 0.0132 - acc: 0.9963 - val_loss: 0.0670 - val_acc: 0.9883
Epoch 44/100
8209/8209 [==============================] - 23s - loss: 0.0188 - acc: 0.9942 - val_loss: 0.0426 - val_acc: 0.9917
Epoch 45/100
8209/8209 [==============================] - 23s - loss: 0.0144 - acc: 0.9948 - val_loss: 0.0605 - val_acc: 0.9883
Epoch 46/100
8209/8209 [==============================] - 23s - loss: 0.0145 - acc: 0.9960 - val_loss: 0.0540 - val_acc: 0.9912
Epoch 47/100
8209/8209 [==============================] - 23s - loss: 0.0120 - acc: 0.9961 - val_loss: 0.0574 - val_acc: 0.9903
Epoch 48/100
8209/8209 [==============================] - 23s - loss: 0.0130 - acc: 0.9954 - val_loss: 0.0526 - val_acc: 0.9927
Epoch 49/100
8209/8209 [==============================] - 23s - loss: 0.0092 - acc: 0.9972 - val_loss: 0.0604 - val_acc: 0.9893
Epoch 50/100
8209/8209 [==============================] - 23s - loss: 0.0154 - acc: 0.9959 - val_loss: 0.0591 - val_acc: 0.9898
Epoch 51/100
8209/8209 [==============================] - 23s - loss: 0.0178 - acc: 0.9945 - val_loss: 0.0613 - val_acc: 0.9888
Epoch 52/100
8209/8209 [==============================] - 23s - loss: 0.0064 - acc: 0.9979 - val_loss: 0.0511 - val_acc: 0.9907
Epoch 53/100
8209/8209 [==============================] - 23s - loss: 0.0067 - acc: 0.9977 - val_loss: 0.0582 - val_acc: 0.9907
Epoch 54/100
8209/8209 [==============================] - 23s - loss: 0.0155 - acc: 0.9965 - val_loss: 0.0576 - val_acc: 0.9878
Epoch 55/100
8209/8209 [==============================] - 23s - loss: 0.0125 - acc: 0.9963 - val_loss: 0.0509 - val_acc: 0.9907
Epoch 56/100
8209/8209 [==============================] - 23s - loss: 0.0050 - acc: 0.9987 - val_loss: 0.0535 - val_acc: 0.9927
Epoch 57/100
8209/8209 [==============================] - 23s - loss: 0.0075 - acc: 0.9978 - val_loss: 0.0496 - val_acc: 0.9912
Epoch 58/100
8209/8209 [==============================] - 24s - loss: 0.0134 - acc: 0.9954 - val_loss: 0.0608 - val_acc: 0.9903
Epoch 59/100
8209/8209 [==============================] - 23s - loss: 0.0093 - acc: 0.9966 - val_loss: 0.0554 - val_acc: 0.9898
Epoch 60/100
8209/8209 [==============================] - 24s - loss: 0.0154 - acc: 0.9959 - val_loss: 0.0552 - val_acc: 0.9898
Epoch 61/100
8209/8209 [==============================] - 23s - loss: 0.0180 - acc: 0.9955 - val_loss: 0.0688 - val_acc: 0.9878
Epoch 62/100
8209/8209 [==============================] - 23s - loss: 0.0151 - acc: 0.9963 - val_loss: 0.0600 - val_acc: 0.9907
Epoch 63/100
8209/8209 [==============================] - 23s - loss: 0.0102 - acc: 0.9968 - val_loss: 0.0656 - val_acc: 0.9903
Epoch 64/100
8209/8209 [==============================] - 23s - loss: 0.0100 - acc: 0.9962 - val_loss: 0.0574 - val_acc: 0.9883
Epoch 65/100
8209/8209 [==============================] - 23s - loss: 0.0090 - acc: 0.9971 - val_loss: 0.0590 - val_acc: 0.9883
Epoch 66/100
8209/8209 [==============================] - 23s - loss: 0.0161 - acc: 0.9959 - val_loss: 0.0519 - val_acc: 0.9912
Epoch 67/100
8209/8209 [==============================] - 24s - loss: 0.0103 - acc: 0.9966 - val_loss: 0.0522 - val_acc: 0.9907
Epoch 68/100
8209/8209 [==============================] - 24s - loss: 0.0093 - acc: 0.9971 - val_loss: 0.0514 - val_acc: 0.9898
Epoch 69/100
8209/8209 [==============================] - 23s - loss: 0.0097 - acc: 0.9971 - val_loss: 0.0588 - val_acc: 0.9898
Epoch 70/100
8209/8209 [==============================] - 23s - loss: 0.0085 - acc: 0.9978 - val_loss: 0.0588 - val_acc: 0.9888
Epoch 71/100
8209/8209 [==============================] - 23s - loss: 0.0056 - acc: 0.9985 - val_loss: 0.0541 - val_acc: 0.9893
Epoch 72/100
8209/8209 [==============================] - 23s - loss: 0.0047 - acc: 0.9985 - val_loss: 0.0571 - val_acc: 0.9898
Epoch 73/100
8209/8209 [==============================] - 23s - loss: 0.0069 - acc: 0.9973 - val_loss: 0.0608 - val_acc: 0.9903
Epoch 74/100
8209/8209 [==============================] - 23s - loss: 0.0080 - acc: 0.9977 - val_loss: 0.0484 - val_acc: 0.9912
Epoch 75/100
8209/8209 [==============================] - 23s - loss: 0.0076 - acc: 0.9976 - val_loss: 0.0535 - val_acc: 0.9903
Epoch 76/100
8209/8209 [==============================] - 23s - loss: 0.0048 - acc: 0.9988 - val_loss: 0.0528 - val_acc: 0.9907
Epoch 77/100
8209/8209 [==============================] - 24s - loss: 0.0100 - acc: 0.9972 - val_loss: 0.0577 - val_acc: 0.9907
Epoch 78/100
8209/8209 [==============================] - 23s - loss: 0.0079 - acc: 0.9976 - val_loss: 0.0590 - val_acc: 0.9893
Epoch 79/100
8209/8209 [==============================] - 23s - loss: 0.0097 - acc: 0.9967 - val_loss: 0.0567 - val_acc: 0.9907
Epoch 80/100
8209/8209 [==============================] - 23s - loss: 0.0128 - acc: 0.9968 - val_loss: 0.0594 - val_acc: 0.9893
Epoch 81/100
8209/8209 [==============================] - 24s - loss: 0.0073 - acc: 0.9977 - val_loss: 0.0566 - val_acc: 0.9903
Epoch 82/100
8209/8209 [==============================] - 24s - loss: 0.0062 - acc: 0.9979 - val_loss: 0.0511 - val_acc: 0.9917
Epoch 83/100
8209/8209 [==============================] - 23s - loss: 0.0034 - acc: 0.9989 - val_loss: 0.0572 - val_acc: 0.9903
Epoch 84/100
8209/8209 [==============================] - 24s - loss: 0.0115 - acc: 0.9967 - val_loss: 0.0556 - val_acc: 0.9898
Epoch 85/100
8209/8209 [==============================] - 23s - loss: 0.0054 - acc: 0.9979 - val_loss: 0.0560 - val_acc: 0.9907
Epoch 86/100
8209/8209 [==============================] - 23s - loss: 0.0112 - acc: 0.9970 - val_loss: 0.0555 - val_acc: 0.9883
Epoch 87/100
8209/8209 [==============================] - 23s - loss: 0.0075 - acc: 0.9971 - val_loss: 0.0501 - val_acc: 0.9903
Epoch 88/100
8209/8209 [==============================] - 23s - loss: 0.0082 - acc: 0.9976 - val_loss: 0.0494 - val_acc: 0.9893
Epoch 89/100
8209/8209 [==============================] - 23s - loss: 0.0048 - acc: 0.9982 - val_loss: 0.0532 - val_acc: 0.9893
Epoch 90/100
8209/8209 [==============================] - 23s - loss: 0.0096 - acc: 0.9968 - val_loss: 0.0586 - val_acc: 0.9893
Epoch 91/100
8209/8209 [==============================] - 23s - loss: 0.0060 - acc: 0.9981 - val_loss: 0.0614 - val_acc: 0.9898
Epoch 92/100
8209/8209 [==============================] - 23s - loss: 0.0070 - acc: 0.9973 - val_loss: 0.0624 - val_acc: 0.9873
Epoch 93/100
8209/8209 [==============================] - 24s - loss: 0.0063 - acc: 0.9978 - val_loss: 0.0550 - val_acc: 0.9898
Epoch 94/100
8209/8209 [==============================] - 24s - loss: 0.0148 - acc: 0.9952 - val_loss: 0.0504 - val_acc: 0.9922
Epoch 95/100
8209/8209 [==============================] - 23s - loss: 0.0039 - acc: 0.9989 - val_loss: 0.0625 - val_acc: 0.9898
Epoch 96/100
8209/8209 [==============================] - 24s - loss: 0.0033 - acc: 0.9990 - val_loss: 0.0667 - val_acc: 0.9907
Epoch 97/100
8209/8209 [==============================] - 23s - loss: 0.0049 - acc: 0.9989 - val_loss: 0.0659 - val_acc: 0.9907
Epoch 98/100
8209/8209 [==============================] - 23s - loss: 0.0078 - acc: 0.9977 - val_loss: 0.0716 - val_acc: 0.9898
Epoch 99/100
8209/8209 [==============================] - 23s - loss: 0.0054 - acc: 0.9987 - val_loss: 0.0611 - val_acc: 0.9917
Epoch 100/100
8209/8209 [==============================] - 22s - loss: 0.0040 - acc: 0.9983 - val_loss: 0.0586 - val_acc: 0.9903
test log：
8209 train samples
2053 valid samples
1292 test samples
1292/1292 [==============================] - 1s
acc: 98.76%