random word masking index shouble be great than 0
## Information

https://github.com/huggingface/transformers/blob/05fa1a7ac17bb7aa07b9e0c1e138ecb31a28bbfe/src/transformers/data/data_collator.py#L771

This line should be:
```python
random_words = torch.randint(1, len(self.tokenizer), labels.shape, dtype=torch.long)
```
because random word masking index should be great than 0 (0 means [PAD] in bert's vocabulary).

I found the bug when I want to change masked input_ids to tokens using tokenizer.convert_ids_to_tokens. If replace a masked id by 0, and then convert_ids_to_tokens, all tokens after 0 will be discarded.

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.15.0
- Platform: Linux-5.4.0-62-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.2
- PyTorch version (GPU?): 1.10.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <False>
- Using distributed or parallel set-up in script?: <False>

cc @sgugger <|||||>I don't think there is anything in the research article or the original pretraining code that excludes the pad token from the random words, so I would leave this as is. You can use your own data collator with any modification you want :-)<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.