MobileBertForSequenceClassification outputs super-high logits
## Environment info
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- `transformers` version: 4.0.0
- Platform: Ubuntu 20.04
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.0
- Tensorflow version (GPU?): None
- Using GPU in script?: True
- Using distributed or parallel set-up in script?: False

### Who can help
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@LysandreJik 

## Information

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

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: please see an example below

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: simple text classification using documents from sec.gov

## To reproduce

Steps to reproduce the behavior:

I am training a whole-text classifier with MobileBert using MobileBertForSequenceClassification:
```{python}
from transformers import MobileBertForSequenceClassification, \
                                        MobileBertTokenizerFast

ARCH = 'google/mobilebert-uncased'

model = MobileBertForSequenceClassification.from_pretrained(ARCH).cuda()
tokenizer = MobileBertTokenizerFast.from_pretrained(ARCH)

x = tokenizer(['def hello(): return "world"', 'This is some test'],
              max_length=512,
              truncation=True,
              return_tensors='pt',
              padding='longest')

with torch.no_grad():
    l = model(**x.to(model.device)).logits 
```
Resulting model outputs are extremely high:
```
tensor([[ 3289181.7500, -2371234.0000],
        [ 3198336.7500, -1882639.8750]])
```
Loading model and tokenizer with Auto- classes gives the same result. 
When using pooled output from ModileBertModel with a custom linear head (BatchNorm1d+Dropout+Linear) everything works fine.

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## Expected behavior

I expect logits to be near [-3, 3], but not in 6-7 digits.

I see the same behavior when trying it out with IMDB classification. 
I solved it by passing `classifier_activation=True` for the `from_pretrained` function. 
[Documentation](https://huggingface.co/transformers/model_doc/mobilebert.html#mobilebertconfig) says it is `True` by default, however it does not seem like it. 
[EDIT] Apparently this changes the behavior of the pooling layer <|||||>@hfawaz Thank you for solving this issue, it's very helpful<|||||>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.