<jupyter_start><jupyter_text>往前微調幾層<jupyter_code>for n in ["block5_conv1", "block5_conv2", "block5_conv3"]:
    model.get_layer(n).trainable = True
from keras.optimizers import Adam
model.compile(optimizer=Adam(lr=0.0001), loss='categorical_crossentropy', metrics=["accuracy"])
model.fit_generator(generate(train_X, train_Y), steps_per_epoch=500, epochs=10, validation_data=v_data)<jupyter_output>Epoch 1/10
500/500 [==============================] - 195s - loss: 0.0804 - acc: 0.9742 - val_loss: 0.0618 - val_acc: 0.9795
Epoch 2/10
 39/500 [=>............................] - ETA: 161s - loss: 0.0610 - acc: 0.9784
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