unexpected keyword argument 'lm_labels' when using BertModel as Decoder with EncoderDecoderModel
The `BertModel.forward()` method does not expect a `lm_labels` and `masked_lm_labels` arguments. Yet, it looks like the `EncoderDecoderModel.forward()` method calls it's decoder's `forward()` method with those arguments which throws a TypeError when a BertModel is used as a decoder.

Am I using the BertModel incorrectly? I can get rid of the error by modifying the EncoderDecoderModel to not use those arguments for the decoder.

Exact Error:

```
File "/Users/utkarsh/anaconda3/envs/py37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/Users/utkarsh/Projects/ai4code/transformers/bert2bert/models.py", line 12, in forward
    dec_out, dec_cls, enc_out, enc_cls = self.bertmodel(input_ids=inputs, attention_mask=input_masks, decoder_input_ids=targets, decoder_attention_mask=target_masks)
  File "/Users/utkarsh/anaconda3/envs/py37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/Users/utkarsh/anaconda3/envs/py37/lib/python3.7/site-packages/transformers/modeling_encoder_decoder.py", line 283, in forward
    **kwargs_decoder,
  File "/Users/utkarsh/anaconda3/envs/py37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
TypeError: forward() got an unexpected keyword argument 'lm_labels'
```

Relevant part of the code:
```
encoder = BertModel(enc_config)
dec_config = BertConfig(...,is_decoder=True)
decoder = BertModel(dec_config)
model = EncoderDecoderModel(encoder=encoder, decoder=decoder)
```
...
`dec_out, dec_cls, enc_out, enc_cls = model(input_ids=inputs, attention_mask=input_masks, decoder_input_ids=targets, decoder_attention_mask=target_masks)`



I'm facing the same problem. Since #4874 it seems like it should be just `labels` instead of `lm_labels`. According to the documentation it should do masked language modeling-loss, but from my debugging it seems like it actually does next word prediction-loss.<|||||>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.
