Stop training when a monitored quantity has stopped improving.
callback_early_stopping(monitor = "val_loss", min_delta = 0, patience = 0,
verbose = 0, mode = c("auto", "min", "max"))quantity to be monitored.
minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.
number of epochs with no improvement after which training will be stopped.
verbosity mode, 0 or 1.
one of "auto", "min", "max". In min mode, training will stop when
the quantity monitored has stopped decreasing; in max mode it will stop
when the quantity monitored has stopped increasing; in auto mode, the
direction is automatically inferred from the name of the monitored
quantity.
Other callbacks: callback_csv_logger,
callback_lambda,
callback_learning_rate_scheduler,
callback_model_checkpoint,
callback_progbar_logger,
callback_reduce_lr_on_plateau,
callback_remote_monitor,
callback_tensorboard,
callback_terminate_on_naan