Incorrect question answering initialization
### System Info

- `transformers` version: 4.26.1
- Platform: Linux-5.15.0-1031-azure-x86_64-with-glibc2.17
- Python version: 3.8.16
- Huggingface_hub version: 0.13.3
- PyTorch version (GPU?): 1.13.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help?

@ArthurZucker
@younesbelkada
@sgugger

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

1. Select deberta-mnli model and perform finetuning for question answering on any dataset
2. Errors out with this message
`
  File "XXXXXX/lib/python3.8/site-packages/transformers/models/deberta/modeling_deberta.py", line 1416, in forward
    start_logits, end_logits = logits.split(1, dim=-1)
ValueError: too many values to unpack (expected 2)
`


Models finetuned on mnli have 3 classes by default in their config file (because mnli dataset has 3 classes). When these models are repurposed for question answering task, the classification head is initialized from the *config file* [here](https://github.com/huggingface/transformers/blob/ae54e3c3b18bac0832ad62ea9b896dfd52a09850/src/transformers/models/deberta/modeling_deberta.py#L1362
)
But for question answering task, 2 outputs per token are expected [here](https://github.com/huggingface/transformers/blob/ae54e3c3b18bac0832ad62ea9b896dfd52a09850/src/transformers/models/deberta/modeling_deberta.py#L1416). So there is a mismatch between model head which is initialized with 3 labels.
This is likely causing an issue with deberta-mnli when used for question answering. It might potentially cause a similar issue for models trained on datasets other than mnli and having number of labels != 2


### Expected behavior

For question answering task, should the num_labels be hardcoded to 2?
This is a bug indeed. Do you want to make a quick PR with your fix (labels should indeed be hardcoded at 2 for question answering)?<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.