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()