Class EarlyStopping
Inherits From: Callback
Defined in tensorflow/python/keras/callbacks.py
.
Stop training when a monitored quantity has stopped improving.
Arguments:
monitor
: Quantity to be monitored.min_delta
: 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.patience
: Number of epochs with no improvement after which training will be stopped.verbose
: verbosity mode.mode
: One of{"auto", "min", "max"}
. Inmin
mode, training will stop when the quantity monitored has stopped decreasing; inmax
mode it will stop when the quantity monitored has stopped increasing; inauto
mode, the direction is automatically inferred from the name of the monitored quantity.baseline
: Baseline value for the monitored quantity. Training will stop if the model doesn't show improvement over the baseline.restore_best_weights
: Whether to restore model weights from the epoch with the best value of the monitored quantity. If False, the model weights obtained at the last step of training are used.
__init__
__init__(
monitor='val_loss',
min_delta=0,
patience=0,
verbose=0,
mode='auto',
baseline=None,
restore_best_weights=False
)
Initialize self. See help(type(self)) for accurate signature.
Methods
tf.keras.callbacks.EarlyStopping.get_monitor_value
get_monitor_value(logs)
tf.keras.callbacks.EarlyStopping.on_batch_begin
on_batch_begin(
batch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_batch_end
on_batch_end(
batch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_epoch_begin
on_epoch_begin(
epoch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_epoch_end
on_epoch_end(
epoch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_train_batch_begin
on_train_batch_begin(
batch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_train_batch_end
on_train_batch_end(
batch,
logs=None
)
tf.keras.callbacks.EarlyStopping.on_train_begin
on_train_begin(logs=None)
tf.keras.callbacks.EarlyStopping.on_train_end
on_train_end(logs=None)
tf.keras.callbacks.EarlyStopping.set_model
set_model(model)
tf.keras.callbacks.EarlyStopping.set_params
set_params(params)