Loading 'fmikaelian/flaubert-base-uncased-squad' throws unexpected, difficult to comprehend warning
## Environment info
     
- `transformers` version: 3.0.2
- Platform: Windows 10 Home v2004, Conda 4.8.3, Anaconda CLI 1.7.2
- Python version: 3.7.1
- PyTorch version (GPU?): 1.6.0 CUDA GPU
- Tensorflow version (GPU?): none
- Using GPU in script?: torch.set_default_tensor_type('torch.cuda.FloatTensor')
- Using distributed or parallel set-up in script?: dunno

### Who can help
@fmikaelian @julien-c 

## Information

Model I am using : FlauBERT

The problem arises when using the official example script.

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: loading 'fmikaelian/flaubert-base-uncased-squad'

## To reproduce

Steps to reproduce the behavior:
```
model_name = 'fmikaelian/flaubert-base-uncased-squad' #flaubert/flaubert_base_cased #flaubert/flaubert_large_cased
config = AutoConfig.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForQuestionAnswering.from_pretrained(model_name, config=config)
```

> Some weights of the model checkpoint at fmikaelian/flaubert-base-uncased-squad were not used when initializing FlaubertForQuestionAnsweringSimple: ['qa_outputs.start_logits.dense.weight', 'qa_outputs.start_logits.dense.bias', 'qa_outputs.end_logits.dense_0.weight', 'qa_outputs.end_logits.dense_0.bias', 'qa_outputs.end_logits.LayerNorm.weight', 'qa_outputs.end_logits.LayerNorm.bias', 'qa_outputs.end_logits.dense_1.weight', 'qa_outputs.end_logits.dense_1.bias', 'qa_outputs.answer_class.dense_0.weight', 'qa_outputs.answer_class.dense_0.bias', 'qa_outputs.answer_class.dense_1.weight']
> - This IS expected if you are initializing FlaubertForQuestionAnsweringSimple from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPretraining model).
> - This IS NOT expected if you are initializing FlaubertForQuestionAnsweringSimple from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
> Some weights of FlaubertForQuestionAnsweringSimple were not initialized from the model checkpoint at fmikaelian/flaubert-base-uncased-squad and are newly initialized: ['qa_outputs.weight', 'qa_outputs.bias']
> You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

## Expected behavior

Not throwing a warning.
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.
