1 | import os |
--2019-02-13 14:04:55-- https://storage.googleapis.com/mledu-datasets/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5
Resolving storage.googleapis.com... 2607:f8b0:4003:c05::80, 64.233.168.128
Connecting to storage.googleapis.com|2607:f8b0:4003:c05::80|:443... connected.
WARNING: cannot verify storage.googleapis.com's certificate, issued by 'CN=Google Internet Authority G3,O=Google Trust Services,C=US':
Unable to locally verify the issuer's authority.
HTTP request sent, awaiting response... 200 OK
Length: 87910968 (84M) [application/x-hdf]
Saving to: '/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5'
/tmp/inception_v3_w 100%[=====================>] 83.84M 75.6MB/s in 1.1s
2019-02-13 14:04:56 (75.6 MB/s) - '/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5' saved [87910968/87910968]
('last layer output shape: ', (None, 7, 7, 768))
1 | from tensorflow.keras.optimizers import RMSprop |
1 | !wget --no-check-certificate \ |
--2019-02-13 14:05:24-- https://storage.googleapis.com/mledu-datasets/cats_and_dogs_filtered.zip
Resolving storage.googleapis.com... 2607:f8b0:4003:c0a::80, 173.194.223.128
Connecting to storage.googleapis.com|2607:f8b0:4003:c0a::80|:443... connected.
WARNING: cannot verify storage.googleapis.com's certificate, issued by 'CN=Google Internet Authority G3,O=Google Trust Services,C=US':
Unable to locally verify the issuer's authority.
HTTP request sent, awaiting response... 200 OK
Length: 68606236 (65M) [application/zip]
Saving to: '/tmp/cats_and_dogs_filtered.zip'
/tmp/cats_and_dogs_ 100%[=====================>] 65.43M 168MB/s in 0.4s
2019-02-13 14:05:24 (168 MB/s) - '/tmp/cats_and_dogs_filtered.zip' saved [68606236/68606236]
Found 2000 images belonging to 2 classes.
Found 1000 images belonging to 2 classes.
1 | history = model.fit_generator( |
Epoch 1/20
100/100 - 17s - loss: 0.5283 - acc: 0.7525 - val_loss: 0.3843 - val_acc: 0.8940
Epoch 2/20
100/100 - 14s - loss: 0.3678 - acc: 0.8340 - val_loss: 0.2040 - val_acc: 0.9480
Epoch 3/20
100/100 - 15s - loss: 0.3352 - acc: 0.8535 - val_loss: 0.3987 - val_acc: 0.9270
Epoch 4/20
100/100 - 15s - loss: 0.3432 - acc: 0.8550 - val_loss: 0.2987 - val_acc: 0.9440
Epoch 5/20
100/100 - 15s - loss: 0.3391 - acc: 0.8640 - val_loss: 0.3390 - val_acc: 0.9450
Epoch 6/20
100/100 - 14s - loss: 0.3135 - acc: 0.8680 - val_loss: 0.3465 - val_acc: 0.9480
Epoch 7/20
100/100 - 14s - loss: 0.3113 - acc: 0.8700 - val_loss: 0.3115 - val_acc: 0.9530
Epoch 8/20
100/100 - 15s - loss: 0.2901 - acc: 0.8820 - val_loss: 0.5042 - val_acc: 0.9370
Epoch 9/20
100/100 - 15s - loss: 0.2912 - acc: 0.8865 - val_loss: 0.3065 - val_acc: 0.9620
Epoch 10/20
100/100 - 15s - loss: 0.2944 - acc: 0.8760 - val_loss: 0.2641 - val_acc: 0.9640
Epoch 11/20
100/100 - 14s - loss: 0.2831 - acc: 0.8810 - val_loss: 0.4515 - val_acc: 0.9450
Epoch 12/20
100/100 - 15s - loss: 0.2682 - acc: 0.8895 - val_loss: 0.3231 - val_acc: 0.9580
Epoch 13/20
100/100 - 15s - loss: 0.2748 - acc: 0.8840 - val_loss: 0.2427 - val_acc: 0.9680
Epoch 14/20
100/100 - 15s - loss: 0.2669 - acc: 0.8945 - val_loss: 0.3075 - val_acc: 0.9630
Epoch 15/20
100/100 - 15s - loss: 0.2732 - acc: 0.8910 - val_loss: 0.2629 - val_acc: 0.9620
Epoch 16/20
100/100 - 14s - loss: 0.2634 - acc: 0.8940 - val_loss: 0.3864 - val_acc: 0.9570
Epoch 17/20
100/100 - 14s - loss: 0.2473 - acc: 0.9040 - val_loss: 0.2648 - val_acc: 0.9670
Epoch 18/20
100/100 - 15s - loss: 0.2767 - acc: 0.8890 - val_loss: 0.2519 - val_acc: 0.9620
Epoch 19/20
100/100 - 17s - loss: 0.2660 - acc: 0.8990 - val_loss: 0.2495 - val_acc: 0.9680
Epoch 20/20
100/100 - 15s - loss: 0.2535 - acc: 0.9020 - val_loss: 0.2682 - val_acc: 0.9670
1 | import matplotlib.pyplot as plt |
<matplotlib.figure.Figure at 0x7ff19c530b90>