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学习率预热

• 在预热期间，学习率从0线性增加到优化器中的初始lr。

• 在预热阶段之后创建一个schedule，使其学习率从优化器中的初始lr线性降低到0

Parameters

• 
optimizer (Optimizer)

  – The optimizer for which to schedule the learning rate.

• 
num_warmup_steps (int)

  – The number of steps for the warmup phase.

• 
num_training_steps (int)

  – The total number of training steps.

• 
last_epoch (int, optional, defaults to -1)

  – The index of the last epoch when resuming training.

Returns

• 
torch.optim.lr_scheduler.LambdaLR

  with the appropriate schedule.

# training steps 的数量: [number of batches] x [number of epochs].
total_steps = len(train_dataloader) * epochs

# 设计 learning rate scheduler
scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps = 50, 
                                            num_training_steps = total_steps)