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.
See also
Other optimizers: optimizer_adadelta,
optimizer_adagrad,
optimizer_adamax,
optimizer_adam,
optimizer_nadam,
optimizer_rmsprop