All learning rates are 0 warning
- `transformers` version: 3.0.2
- Platform: Linux
- Python version: 3.6
- PyTorch version (GPU?): 1.4 (GPU)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
@sshleifer 

## Information

Model I am using (Bert, XLNet ...): BART

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. Running the example script in https://github.com/huggingface/transformers/tree/master/examples/seq2seq (finetune_bart_tiny.sh), I'm getting this warning in the beginning of training. However, the training process is continuing after that. 

Warning:
```
finetune.py:245: UserWarning: All learning rates are 0
  warnings.warn("All learning rates are 0")
Epoch 1:   0%|      
/home/sajad/anaconda3/lib/python3.6/site-packages/torch/optim/lr_scheduler.py:224: UserWarning: To get the last learning rate computed by the scheduler, please use `get_last_lr()`.
  warnings.warn("To get the last learning rate computed by the scheduler, "
```

## Expected behavior
While the training seemingly goes well, I'm wondering if this warning would cause problems, leading to deteriorate model's final performance? As a add-on, I've also incorporated the gradient checkpointing to some computational blocks of BART (modifying `modelling_bart.py` script a bit). But even w/o incorporating this module, I'm still getting this warning message? Any thoughts of how to solve it? 

Duplicate of #5338 , ignore it.
Sorry for the confusion.<|||||>It makes sense what you answered at #5338, thanks for the clarification. I'm closing this issue!