R/optimizers.R

optimizer_sgd

Stochastic gradient descent optimizer

Description

Stochastic gradient descent optimizer with support for momentum, learning rate decay, and Nesterov momentum.

Usage

 
optimizer_sgd( 
  learning_rate = 0.01, 
  momentum = 0, 
  decay = 0, 
  nesterov = FALSE, 
  clipnorm = NULL, 
  clipvalue = NULL, 
  ... 
) 

Arguments

Arguments Description
learning_rate float >= 0. Learning rate.
momentum float >= 0. Parameter that accelerates SGD in the relevant direction and dampens oscillations.
decay float >= 0. Learning rate decay over each update.
nesterov boolean. Whether to apply Nesterov momentum.
clipnorm Gradients will be clipped when their L2 norm exceeds this value.
clipvalue Gradients will be clipped when their absolute value exceeds this value.
Unused, present only for backwards compatability

Value

Optimizer for use with compile.keras.engine.training.Model.

See Also

Other optimizers: optimizer_adadelta(), optimizer_adagrad(), optimizer_adamax(), optimizer_adam(), optimizer_nadam(), optimizer_rmsprop()