QA examples fixing & clean-up:
Thank you for the great library! I had to clean up QA examples, because of the duplicate pre- and post-processing code. However, while doing so I have encountered a number of issues that I had to fix. Please, see details below.

# What does this PR do?

1. refactoring: consolidating duplicate post-processing functions in a helper file (now shared between regular and no-trainer version)
2. Fixes evaluation errors popping up when you train/eval on squad v2-eval : utils_qa.py (one was newly encountered and one that was previously reported #15401).
3. Fixes SQuAD unit tests and ensures all boolean arguments use store_true. Please, don't use boolean arguments that don't use store_true. False or false or any non-empty string is being converted to True in this case and this clearly is not the desired behavior.
4. all **no-trainer** test scripts are now saving metric values in the same way (with the right prefix ``eval_``). Previously, because of the bug described in item 3, the unit test was using SQuAD v2 metrics instead of SQuAD v1 metrics. v2 uses different metric name for the exact match. This was previously "fixed" at the level of the ``run_qa_no_trainer.py``. However, such a fix isn't necessary any more.
5. Adds forgotten model.eval() in the **no-trainer** versions. This fully fixed training of the **no-trainer**
variant for the regular squad QA model **without** beam search. In the case of **using beam-search** the gap decreased, but not fully. Yet it is small. Unfortunately, the beam-search SQuAD v2 version produces strange numbers (the older code is even worse), so this requires extra investigation IMHO. Please, see the F1 scores and the discussion below.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] You make sure to update the documentation with your changes? **I believe examples aren't covered by the documentation** 
- [X] Did you write any new necessary tests? **I trained squad and squad v2 models and compared results (see the discussion below)**, but I am not sure if any new tests are needed. I also **fixed** a unit test so it uses the proper SQuAD (v1) metric.


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Perhaps, this can be of most interest for  @sgugger, @patil-suraj.

## Comparing old and new performance

Some remaining issues:
1. Despite the fixes & improvements, there's still a discrepancy between no-trainer and original version for SQuAD v2 or the beam-search version.
2. In particular, for SQuAD v2 and the beam-search variant **without trainer**, both old and new numbers look very wrong to me.

Please note that to be able to run SQuAD v2 tests, **I had to apply utils_qa.py fixes to the old code as well**. Otherwise, it would have just failed:

The metric is F1, the exact scores have the same pattern.

|                                   | previous | fixed |
|-----------------------------------|----------|-------|
| squad v1                          |     88.4 |  88.4 |
| squad v1 (no trainer)             |     86.7 |  88.5 |
| squad v1 (beam search)            |     92.1 |  92.1 |
| squad v1 (beam search no trainer) |     90.2 |  91.0 |
| squad v2 (beam search)            |     83.2 |  83.2 |
| squad v2 (beam search no trainer) |      4.9 |  50.1 |
_The documentation is not available anymore as the PR was closed or merged._