Documentation and code mismatch in BertForMaskedLM forward method
# 🐛 Bug

## Information

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

BertForMaskedLM

Language I am using the model on (English, Chinese ...):

Not important.

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

The tasks I am working on is:

I am trying to obtain LM probabilities for research purposes.

## To reproduce

Steps to reproduce the behavior:

1. According to the documentation, the code below should work as expected.

However, masked_lm_loss and ltr_lm_loss values are in fact in 2nd and 1st positions. This is apparent if the code is inspected, i.e. lm_labels related code is executed after masked_lm_labels related code.

See https://github.com/huggingface/transformers/blob/908fa43b543cf52a3238129624f502240725a6a6/src/transformers/modeling_bert.py#L1001-L1014

and

https://github.com/huggingface/transformers/blob/908fa43b543cf52a3238129624f502240725a6a6/src/transformers/modeling_bert.py#L1014

The following code is an excerpt from my code.

```python
model = BertForMaskedLM.from_pretrained('bert-base-cased')
with torch.no_grad():
    outputs = model(token_ids_in_sentence_tensor,
                    masked_lm_labels=token_ids_in_sentence_tensor,
                            lm_labels=token_ids_in_sentence_tensor,
                            token_type_ids=segments_tensors)
    masked_lm_loss = outputs[0]
    ltr_lm_loss = outputs[1]
    predictions = outputs[2]
```

## Expected behavior

Explained above.

## Environment info
     
- `transformers` version:
- Platform: Darwin XXX-3.local 19.3.0 Darwin Kernel Version 19.3.0: Thu Jan  9 20:58:23 PST 2020; root:xnu-6153.81.5~1/RELEASE_X86_64 x86_64
- Python version: 3.7.4
- PyTorch version (GPU?): no GPU, 1.3.1
- Tensorflow version (GPU?): 2.0.0
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
