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# Optimization

The `.optimization` module provides:

- an optimizer with weight decay fixed that can be used to fine-tuned models, and
- several schedules in the form of schedule objects that inherit from `_LRSchedule`:
- a gradient accumulation class to accumulate the gradients of multiple batches


## AdaFactor (PyTorch)

[[autodoc]] Adafactor

## AdamWeightDecay (TensorFlow)

[[autodoc]] AdamWeightDecay

[[autodoc]] create_optimizer

## Schedules

### Learning Rate Schedules (PyTorch)

[[autodoc]] SchedulerType

[[autodoc]] get_scheduler

[[autodoc]] get_constant_schedule

[[autodoc]] get_constant_schedule_with_warmup

<img alt="" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/warmup_constant_schedule.png"/>

[[autodoc]] get_cosine_schedule_with_warmup

<img alt="" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/warmup_cosine_schedule.png"/>

[[autodoc]] get_cosine_with_hard_restarts_schedule_with_warmup

<img alt="" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/warmup_cosine_hard_restarts_schedule.png"/>

[[autodoc]] get_linear_schedule_with_warmup

<img alt="" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/warmup_linear_schedule.png"/>

[[autodoc]] get_polynomial_decay_schedule_with_warmup

[[autodoc]] get_inverse_sqrt_schedule

[[autodoc]] get_wsd_schedule

### Warmup (TensorFlow)

[[autodoc]] WarmUp

## Gradient Strategies

### GradientAccumulator (TensorFlow)

[[autodoc]] GradientAccumulator
