Model Checkpoint and Callback in Keras

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ModelCheckpoint callback is used in conjunction with training using model. fit() to save a model or weights (in a checkpoint file) at some interval, so the model or weights can be loaded later to continue the training from the state saved.
# Checkpoint to save best model per epoch

model_filepath = "/content/drive/My Drive/model-{epoch:02d}-{val_accuracy:.4f}.hdf5"
checkpoint = ModelCheckpoint(
filepath=model_filepath,
monitor='val_accuracy',
mode='max',
save_best_only=True,
verbose=1
)
train_ds,
validation_data=val_ds,
epochs=50,callbacks=[checkpoint]
)
  1. InvesTime
  2. model checkpoint keras
  3. model checkpoint save best only
  4. callback in keras
  5. monitor the performance of the deep learning model
  6. saving deep learning model
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Комментарии
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Your pronunciation is so clear that I can understand it even if my hearing is poor。

曾魁-rn
Автор

how do I continue from last checkpoint?

zenel
Автор

Please show the visible images about check point

bhargavisairmai