DeBERTa can't load some parameters
### System Info

- `transformers` version: 4.21.1
- Platform: Linux-5.4.0-81-generic-x86_64-with-glibc2.31
- Python version: 3.9.12
- Huggingface_hub version: 0.8.1
- PyTorch version (GPU?): 1.11.0+cu113 (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?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help?

@LysandreJik


### Information

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

### Tasks

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

### Reproduction

- Reproduction

```python
from transformers import pipeline

text = "The capital of France is [MASK]"

mlm_pipeline = pipeline('fill-mask', model='microsoft/deberta-base', tokenizer='microsoft/deberta-base')
print(mlm_pipeline(text))
```

- Warning Message
```
Some weights of the model checkpoint at microsoft/deberta-base were not used when initializing DebertaForMaskedLM: ['lm_predictions.lm_head.LayerNorm.bias', 'lm_predictions.lm_head.bias', 'lm_predictions.lm_head.dense.bias', 'lm_predictions.lm_head.dense.weight', 'deberta.embeddings.position_embeddings.weight', 'lm_predictions.lm_head.LayerNorm.weight']
- This IS expected if you are initializing DebertaForMaskedLM 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 DebertaForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of DebertaForMaskedLM were not initialized from the model checkpoint at microsoft/deberta-base and are newly initialized: ['cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.predictions.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
```

- Output
```
The capital of France isumption
The capital of France is�
The capital of France iszag
The capital of France isreply
The capital of France isnerg
```

### Expected behavior

When DeBERTa model load using transformers, It seems that doesn't load the weights needed for the MLM head. (+ positional embedding weights). 
There are some issues similar to mine.
- https://github.com/huggingface/transformers/issues/15216
- https://github.com/huggingface/transformers/issues/15673
- https://github.com/microsoft/DeBERTa/issues/74
  
But it doesn't seem to be working out yet.  
Can you check it?
#18674 should fix this. Thanks for reporting!<|||||>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.