Improved documentation for EarlyStopping/ReduceLROnPlateau, take validation_freq into account.
@@ -739,8 +739,12 @@ class EarlyStopping(Callback):
to qualify as an improvement, i.e. an absolute
change of less than min_delta, will count as no
improvement.
- patience: number of epochs with no improvement
- after which training will be stopped.
+ patience: number of epochs that produced the monitored
+ quantity with no improvement after which training will
+ be stopped.
+ Validation quantities may not be produced for every
+ epoch, if the validation frequency
+ (`model.fit(validation_freq=5)`) is greater than one.
verbose: verbosity mode.
mode: one of {auto, min, max}. In `min` mode,
training will stop when the quantity
@@ -959,8 +963,12 @@ class ReduceLROnPlateau(Callback):
monitor: quantity to be monitored.
factor: factor by which the learning rate will
be reduced. new_lr = lr * factor
- patience: number of epochs with no improvement
- after which learning rate will be reduced.
+ patience: number of epochs that produced the monitored
+ quantity with no improvement after which training will
+ be stopped.
+ Validation quantities may not be produced for every
+ epoch, if the validation frequency
+ (`model.fit(validation_freq=5)`) is greater than one.
verbose: int. 0: quiet, 1: update messages.
mode: one of {auto, min, max}. In `min` mode,
lr will be reduced when the quantity
