EncoderDecoderModel works poorly with Mlflow
## Environment info
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- `transformers` version: 4.0.0

## Description
Mlflow keeps track of model config parameters, EncoderDecoderConfig has `encoder` and `decoder` parameters which are basically configs of encoder and decoder. They are converted first `to_dict` and then to string `str()` by mlflow resulting in a long string that can not be fit. The `MAX_PARAM_VAL_LENGTH` of Mlflow is set to 250 and AFAIK can not be changed. 

This result in an error:
`MlflowException: Param value '{'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'use_bfloat16': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'is_encoder_decoder': False, 'is_decoder': False, 'add_cross_attention': Fa' had length 1669, which exceeded length limit of 250`

My solution for training phase is:
```
class DummyClass:
    def to_dict(self):
        return {}
    
model.config.encoder = DummyClass()
model.config.decoder = DummyClass() 
```
@patrickvonplaten
Thanks for your proposed solution @alexyalunin ! 

I don't really think that this is a problem on our side. I think MLFlow should better handle this no? <|||||>Probably, but since you use mlflow inside your library people might expect it working with your models. I won't open the issue in mlflow repo, I leave it to someone who encounters this error again. @patrickvonplaten You can close this issue then. <|||||>This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.

If you think this still needs to be addressed please comment on this thread.