Changing the docs as per Pytorch v1.1+
## ❓ Questions & Help

[Docs Link](https://huggingface.co/transformers/migration.html#optimizers-bertadam-openaiadam-are-now-adamw-schedules-are-standard-pytorch-schedules)

```
# From the Docs
### In Transformers, optimizer and schedules are splitted and instantiated like this:
optimizer = AdamW(model.parameters(), lr=lr, correct_bias=False)  # To reproduce BertAdam specific behavior set correct_bias=False
scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps=num_warmup_steps, num_training_steps=num_training_steps)  # PyTorch scheduler
### and used like this:
for batch in train_data:
    loss = model(batch)
    loss.backward()
    torch.nn.utils.clip_grad_norm_(model.parameters(), max_grad_norm)  # Gradient clipping is not in AdamW anymore (so you can use amp without issue)
    scheduler.step()
    optimizer.step()
```

As per the Pytorch 1.1+, 

>Prior to PyTorch 1.1.0, the learning rate scheduler was expected to be called before the optimizer’s update; 1.1.0 changed this behavior in a BC-breaking way. If you use the learning rate scheduler (calling scheduler.step()) before the optimizer’s update (calling optimizer.step()), this will skip the first value of the learning rate schedule. If you are unable to reproduce results after upgrading to PyTorch 1.1.0, please check if you are calling scheduler.step() at the wrong time.

[Pytorch Reference Link](https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate)

Thanks.

PS Not sure if the issue category selected is apt.
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
