2.9.0 Padding Bug
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): **Roberta with RobertaForSequenceClassification head**

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

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

**The problem arises when performing a forward pass while training. I assume something is wrong with padding, though with 2.8.0 version it works correctly.**

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

**I'm using pre-trained roBERTa model for classification task. Details can be found in the notebook below.**

## To reproduce

Steps to reproduce the behavior:

1. Run https://colab.research.google.com/drive/1w54ScQ3-dh99-cO4OGG6-IdP4JRfki59?usp=sharing

Error message:

```
     56         # Perform a forward pass
---> 57         loss, logits = model(b_input_ids, token_type_ids=None, attention_mask=b_input_mask, labels=b_labels)

...

   2033     """
   2034     # The series of casts and type-conversions here are carefully balanced to both work with ONNX export and XLA.
-> 2035     mask = input_ids.ne(padding_idx).int()
   2036     incremental_indices = torch.cumsum(mask, dim=1).type_as(mask) * mask
   2037     return incremental_indices.long() + padding_idx

TypeError: ne() received an invalid combination of arguments - got (NoneType), but expected one of:
 * (Tensor other)
      didn't match because some of the arguments have invalid types: (!NoneType!)
 * (Number other)
      didn't match because some of the arguments have invalid types: (!NoneType!)
```

## Expected behavior

It should work without errors. The problem arises after installing 2.9.0 version. With 2.8.0 version it works correctly.

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: **2.9.0**
- Platform: Google colab
- Python version: 3.6.9
- PyTorch version (GPU?): 1.5.0+cu101
- Tensorflow version (GPU?): 2.2.0rc4
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: n/a

Can you provide a smaller reproduction case?<|||||>```
# Downloading pre-trained model
!wget https://github.com/sdadas/polish-roberta/releases/download/models/roberta_base_transformers.zip
!unzip roberta_base_transformers.zip -d roberta_base_transformers
!pip install transformers -q

from tokenizers import SentencePieceBPETokenizer
from tokenizers.processors import RobertaProcessing
from transformers import RobertaModel, AutoModel

# Loading tokenizer
model_dir = "roberta_base_transformers"
tokenizer = SentencePieceBPETokenizer(f"{model_dir}/vocab.json", f"{model_dir}/merges.txt")
getattr(tokenizer, "_tokenizer").post_processor = RobertaProcessing(sep=("</s>", 2), cls=("<s>", 0))

# Loading model
model: RobertaModel = AutoModel.from_pretrained(model_dir)

input = tokenizer.encode("Ala ma kota.")
output = model(torch.tensor([input.ids]))[0]
print(output[0][1])
```
<|||||>same here!
transformers 2.8.0 works fine. but 'transformers >= 2.9.0' produce exactly same error.<|||||>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.
<|||||>trouble shooting
```
position_ids = create_position_ids_from_input_ids(input_ids, self.padding_idx).to(input_ids.device)
mask = input_ids.ne(padding_idx).int()
...
ne() received an invalid combination of arguments - got (NoneType)
```
just modify 'pad_token_id: null' to 'pad_token_id: 1' in `config.json`