# 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 ## AdamW (PyTorch) [[autodoc]] AdamW ## 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 [[autodoc]] get_cosine_schedule_with_warmup [[autodoc]] get_cosine_with_hard_restarts_schedule_with_warmup [[autodoc]] get_linear_schedule_with_warmup [[autodoc]] get_polynomial_decay_schedule_with_warmup [[autodoc]] get_inverse_sqrt_schedule ### Warmup (TensorFlow) [[autodoc]] WarmUp ## Gradient Strategies ### GradientAccumulator (TensorFlow) [[autodoc]] GradientAccumulator