Remove extra self from _save_checkpoint call
Currently this code is completely broken with non-distributed training. I'm not clear on how it has ever worked:

```
  File "run.py", line 152, in <module>
    trainer.train() #resume_from_checkpoint=get_last_checkpoint("/opt/ml/checkpoints"))
  File "/opt/conda/lib/python3.6/site-packages/transformers/trainer.py", line 1105, in train
    self._maybe_log_save_evaluate(tr_loss, model, trial, epoch)
  File "/opt/conda/lib/python3.6/site-packages/transformers/trainer.py", line 1202, in _maybe_log_save_evaluate
    self._save_checkpoint(model, trial, metrics=metrics)
  File "/opt/conda/lib/python3.6/site-packages/transformers/sagemaker/trainer_sm.py", line 245, in _save_checkpoint
    super()._save_checkpoint(self, model, trial, metrics=metrics)
TypeError: _save_checkpoint() got multiple values for argument 'metrics'
```

This is because the `self` argument shouldn't be passed, so `trial` ends up as `metrics` via it's position.
This is a PR against an older version of Transformers, which we do not accept. This code has been completely removed since then and is now fully integrated into Trainer.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.