Change no trainer image_classification test
# What does this PR do?

I noticed that this test has been failing for the last few months, and it's due to the fact that on a single GPU or CPU the tests pass (we hit 50% accuracy), but on multi GPU it's a hit or miss whether or not it does (each epoch/batch is either 50% or 0%, and we happen to miss that coin flip each time).

This PR modifies the no_trainer test to mimic the equivalent pytorch example tests, and I can confirm it passes repeatedly on a single GPU, CPU, and multi GPU: https://github.com/huggingface/transformers/blob/main/examples/pytorch/test_pytorch_examples.py#L390-L417


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] 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.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [x] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@sgugger @NielsRogge 
_The documentation is not available anymore as the PR was closed or merged._<|||||>@sgugger I've addressed the speed concern in the test, but you won't actually see it show up due to a bug in the scheduler step recalculation. I'll open up another PR for that fix and then merge this one after that's done 