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Step Decay#

A learning rate decay optimizer that reduces the global learning rate by a factor whenever it reaches a new floor. The number of steps needed to reach a new floor is defined by the steps hyper-parameter.

Parameters#

# Param Default Type Description
1 rate 0.01 float The learning rate that controls the global step size.
2 steps 100 int The size of every floor in steps. i.e. the number of steps to take before applying another factor of decay.
3 decay 1e-3 float The factor to decrease the learning rate at each floor.

Example#

use Rubix\ML\NeuralNet\Optimizers\StepDecay;

$optimizer = new StepDecay(0.1, 50, 1e-3);