Early stopping callbackSource:
Stops training when a monitored metric stops improving
luz_callback_early_stopping( monitor = "valid_loss", min_delta = 0, patience = 0, mode = "min", baseline = NULL )
A string in the format
<set>can be 'train' or 'valid' and
<metric>can be the abbreviation of any metric that you are tracking during training. The metric name is case insensitive.
Minimum improvement to reset the patience counter.
Number of epochs without improving until stoping training.
Specifies the direction that is considered an improvement. By default 'min' is used. Can also be 'max' (higher is better) and 'zero' (closer to zero is better).
An initial value that will be used as the best seen value in the begining. Model will stopm training if no better than baseline value is found in the first
This callback adds a
on_early_stopping callback that can be used to
call callbacks as soon as the model stops training.
fit.luz_module_generator() a message is printed when