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ResidentMario/train_model.py

Created January 28, 2019 21:55
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train_model.py
import pathlib
sample_size = len(list(pathlib.Path('../data/images_cropped/').rglob('./*')))
batch_size = 16
hist = model.fit_generator(
train_generator,
steps_per_epoch=sample_size // batch_size,
epochs=50,
validation_data=validation_generator,
validation_steps=round(sample_size * 0.2) // batch_size,
callbacks=[EarlyStopping(monitor='val_loss', min_delta=0, patience=4)]
)
model.save("clf.h5")
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