If I use Keras callback ModelCheckpoint, and I put save_best_only = True and period=3, how will the model be saved? After 3 period it saves the best result from that 3 period, or it just saves the best one of all epochs?
Piece of code that I used:
mcp = tf.keras.callbacks.ModelCheckpoint("my_model.h5", monitor="val_accuracy",
save_best_only=True, period=3)
First of all, according to documentation, period argument is deprecated in favor of save_freq argument (which if assigned to an int, it would consider number of seen batches and not the epochs). But for backwards compatibility, the period argument is still working.
But to find out the answer to your question, we need to inspect the source code for ModelCheckpoint callback. Actually, the best value of monitored metric seen so far is updated only if period epochs has passed (since the last checkpoint). And also. since the best metric value seen so far is compared with the monitored metric value of only current epoch, therefore we can conclude that only the best performing model in epochs period, 2*period, 3*period, etc. are compared and saved, and the performance of the model between those epochs is ignored.
Setting period=3 will attempt to save a model every 3 batches. If you want it to save at the end of every epoch, set period='epoch'.
If save_best_only=True it will check to see if the validation accuracy is higher this time than last time and only save that model. If the validation accuracy is not this high, it will not save the model.
Source: https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/ModelCheckpoint#arguments_1