Evaluation results of `run_qa.py` are anormally low
### System Info

- `transformers` version: 4.21.0.dev0
- Platform: Linux-5.15.0-39-generic-x86_64-with-glibc2.35
- Python version: 3.9.12
- Huggingface_hub version: 0.8.1
- PyTorch version (GPU?): 1.11.0+cu102 (False)
- 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?

_No response_

### 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

Do 
* `conda create -n tempoenv python=3.9`
* `git clone https://github.com/huggingface/transformers.git`
* `cd transformers`
* `pip install .[torch]`
* `pip install datasets`


and 
```
python examples/pytorch/question-answering/run_qa.py --model_name_or_path distilbert-base-uncased-distilled-squad \
    --dataset_name squad --do_eval --max_seq_length 384 \
    --doc_stride 128 --output_dir /tmp/debug_squad/
```

giving 

```
***** eval metrics *****
  eval_exact_match =  0.369
  eval_f1          = 0.4673
  eval_samples     =    100
```

which is much lower than what we used to see (about 0.85 f1), see e.g. https://huggingface.co/distilbert-base-uncased-distilled-squad or https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=squad . It's not clear why the eval is only on 100 samples.

### Expected behavior

Higher f1 score
Removing the cached arrow processed dataset solved the issue.