Stochastic gradient descent optimizer

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

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

Arguments

lr	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.

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