Improve notrainer examples
# What does this PR do?
1. In no-trainer examples, `train_loss` being logged wasn't normalized and as such wasn't intuitive to understand. This also made it difficult to compare train loss between different tools such as comparing train loss from Trainer with that of Accelerate. This PR normalizes the train_loss per epoch to make is more intuitive and comparable.
2. Replaces HF AdamW with torch AdamW for NLP no-trainer examples. This prevents corresponding warning being displayed.
3. Fixing no-trainer examples so that tracker run is created only for the main process else wandb will create num_processes runs with no data.
4. converting `train_loss` from tensor to float so that it gets logged in tensorboard tracker
5. Fixing `run_ner_no_trainer.py` to correctly log `train_loss` in `all_results.json`
6. Adding `report_to` arg to enable users to specify preferred tracker instead of all available trackers which is default option. This prevents logging to the trackers that user doesn't want.
7. In many no-trainer NLP tasks one can train model from scratch, this means that user can bypass `model_name_or_path` arg. However, it is set as required for all scripts which throws error when it isn't specified. Setting this arg `required=False` in corresponding examples to resolve the error when training from scratch.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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      Pull Request section?
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      to it if that's the case.
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      [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).
- [ ] Did you write any new necessary tests?
_The documentation is not available anymore as the PR was closed or merged._