`Trainer`'s dataset requires additional arguments when PyTorch version <2
Author: cchan-lm
Pull request: no

### System Info

- `transformers` version: 4.38.1
- Platform: Linux-5.15.0-92-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.20.3
- Safetensors version: 0.4.2
- Accelerate version: 0.27.2
- Accelerate config:    not found
- PyTorch version (GPU?): 1.13.0+cu116 (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?: yes
- Using distributed or parallel set-up in script?: yes

### 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

Run:
```bash
cd transformers/examples/pytorch/question-answering
python run_qa.py --model_name_or_path bert-large-uncased-whole-word-masking-finetuned-squad --dataset_name squad --do_eval --per_device_eval_batch_size 12 --output_dir .
```

This is what I'm seeing in my environment:
| `tranformers` version | `torch` version | outcome |
| --- | --- | --- |
| 4.38.1 / 4.38.0 | 2.2.0 | success |
| 4.38.1 / 4.38.0 | 1.13.1 | requires `--dataloader_num_workers` and `--dataloader_prefetch_factor` (I used 1 and 2, respectively), otherwise fails |
| 4.37.2 | 1.13.1 | success |

We also have code that uses `Trainer` in a similar way to `run_qa.py` that I cannot post here, but running the official example shows the same problem.

Thank you in advance for looking into this!

### Expected behavior

I expect `transformers` to be backwards compatible with PyTorch version <2, otherwise `transformers` should indicate it only supports v2 or above.

Comments:
Hey, not sure what to say, the examples should be adapted to each's use-case! 

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.

My apologies, I had missed the emails regarding this issue. I had this workaround in `run_qa.py` to work with PyTorch < 2:
```python
...
    def compute_metrics(p: EvalPrediction):
        return metric.compute(predictions=p.predictions, references=p.label_ids)

    ##### BEGIN CHANGE #####
    if hasattr(training_args, "dataloader_num_workers") and not training_args.dataloader_num_workers:
        training_args.dataloader_num_workers = 1
    if hasattr(training_args, "dataloader_prefetch_factor") and not training_args.dataloader_prefetch_factor:
        training_args.dataloader_prefetch_factor = 2
    ##### ENDCHANGE #####

    # Initialize our Trainer
    trainer = QuestionAnsweringTrainer(
        model=model,
        args=training_args,
        train_dataset=train_dataset if training_args.do_train else None,
        eval_dataset=eval_dataset if training_args.do_eval else None,
        eval_examples=eval_examples if training_args.do_eval else None,
        tokenizer=tokenizer,
        data_collator=data_collator,
        post_process_function=post_processing_function,
        compute_metrics=compute_metrics,
    )
...
```