Proposal: Update examples to utilize a new format.
This PR creates a new example coding style for the pytorch code. 

* Uses pytorch-lightning for the underlying training. 
* Separates out the base transformer loading from the individual training. 
* Moves each individual example to its own directory. 
* Move the code in the readme to bash scripts. 

The only two new files are `run_pl_ner.py` and `transformers_base.py`.

The goal is to keep the same format as the original command-line. Most of the argument names are preserved. I have verified that for NER the results of the same on GPU. 

There are several nice benefits of lightning -> somewhat nicer logging and library integration (e.g. wandb), auto-checkpointing. Mostly the goal though is code readability with identical functionality. 

Todo: 
* make sure that the output file format is identical. 
* print test results after training. 
* test multi-gpu and apex (in theory these should work) 
Hi @srush, thanks for this PR :heart:  Can't wait to test it!

One suggestion/RFC: could we rename it to something like `token_classification` instead of `ner`. I know PoS tagging is not really covered in recent papers, but I always test new models for this task with the "identical" implementation 😅 This requires only a little modification in the code: we then should report accuracy as well.

But I will be totally fine with `ner` here!<|||||>Token Classification sounds good to me. That is consistent with the internal naming. 