Add warning message for `run_qa.py`
Author: jla524
Pull request: yes

# What does this PR do?

<!--
Congratulations! You've made it this far! You're not quite done yet though.

Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.

Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.

Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->

<!-- Remove if not applicable -->

Fixes #29801 (issue)

When running with `--load_best_model_at_end`, `--metric_for_best_model` is set to `"loss"` by default. However, [loss is not supported by squad](https://github.com/huggingface/evaluate/blob/8dfe05784099fb9af55b8e77793205a3b7c86465/metrics/squad/squad.py#L64) or [squad_v2](https://github.com/huggingface/evaluate/blob/8dfe05784099fb9af55b8e77793205a3b7c86465/metrics/squad_v2/squad_v2.py#L86).

We can throw a warning to let the users know to explicitly set the metric to one supported by squad or squad_v2.

## Who can review?

@ftesser and @ArthurZucker

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @pacman100

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc and @younesbelkada

Documentation: @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Comments:
Thanks @SunMarc! I've updated the PR to raise a warning instead. It'll show a warning like this:

```
/Users/jacky/repos/transformers/examples/pytorch/question-answering/run_qa.py:636: UserWarning: --metric_for_best_model should be set to one of ('exact_match', 'f1')
  warnings.warn(f"--metric_for_best_model should be set to one of {accepted_best_metrics}")
```