View source: R/learning_rate_schedules.R

learning_rate_schedule_inverse_time_decay | R Documentation |

A LearningRateSchedule that uses an inverse time decay schedule

```
learning_rate_schedule_inverse_time_decay(
initial_learning_rate,
decay_steps,
decay_rate,
staircase = FALSE,
...,
name = NULL
)
```

`initial_learning_rate` |
A scalar |

`decay_steps` |
A scalar |

`decay_rate` |
An R number. The decay rate. |

`staircase` |
Boolean. Whether to apply decay in a discrete staircase, as opposed to continuous, fashion. |

`...` |
For backwards and forwards compatibility |

`name` |
String. Optional name of the operation. Defaults to 'InverseTimeDecay'. |

When training a model, it is often useful to lower the learning rate as
the training progresses. This schedule applies the inverse decay function
to an optimizer step, given a provided initial learning rate.
It requires a `step`

value to compute the decayed learning rate. You can
just pass a TensorFlow variable that you increment at each training step.

The schedule is a 1-arg callable that produces a decayed learning rate when passed the current optimizer step. This can be useful for changing the learning rate value across different invocations of optimizer functions. It is computed as:

decayed_learning_rate <- function(step) { initial_learning_rate / (1 + decay_rate * step / decay_step) }

or, if `staircase`

is `TRUE`

, as:

decayed_learning_rate function(step) { initial_learning_rate / (1 + decay_rate * floor(step / decay_step)) }

You can pass this schedule directly into a keras Optimizer
as the `learning_rate`

.

Example: Fit a Keras model when decaying `1/t`

with a rate of `0.5`

:

... initial_learning_rate <- 0.1 decay_steps <- 1.0 decay_rate <- 0.5 learning_rate_fn <- learning_rate_schedule_inverse_time_decay( initial_learning_rate, decay_steps, decay_rate) model %>% compile(optimizer = optimizer_sgd(learning_rate = learning_rate_fn), loss = 'sparse_categorical_crossentropy', metrics = 'accuracy') model %>% fit(data, labels, epochs = 5)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.