TensorFlow 1 version | View source on GitHub |
Learning rate scheduler.
Inherits From: Callback
tf.keras.callbacks.LearningRateScheduler(
schedule, verbose=0
)
Arguments | |
---|---|
schedule
|
a function that takes an epoch index as input (integer, indexed from 0) and returns a new learning rate as output (float). |
verbose
|
int. 0: quiet, 1: update messages. |
# This function keeps the learning rate at 0.001 for the first ten epochs
# and decreases it exponentially after that.
def scheduler(epoch):
if epoch < 10:
return 0.001
else:
return 0.001 * tf.math.exp(0.1 * (10 - epoch))
callback = tf.keras.callbacks.LearningRateScheduler(scheduler)
model.fit(data, labels, epochs=100, callbacks=[callback],
validation_data=(val_data, val_labels))
Methods
set_model
set_model(
model
)
set_params
set_params(
params
)