Trainer.train argument resume_from_last_checkpoint
# 🚀 Feature request

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`Trainer.train` accepts `resume_from_checkpoint` argument, which requires the user to explicitly provide the checkpoint location to continue training from.
`resume_from_last_checkpoint` can be useful to resume training by picking the latest checkpoint from `output_dir` of the `TrainingArguments` passed.

## Motivation

1. The checkpoint directory is created by the library, so user needs to navigate to the directory to find the value to provide for `resume_from_checkpoint`
2. User may just want to resume from the last valid checkpoint since their training got disrupted previously (a common scenario for someone to want to resume training). All they know is the `output_dir` they provided initially

This motivates to provide a `resume_from_last_checkpoint=True` to the `Trainer.train(...)` call, which will pick the latest checkpoint from `args.output_dir`. FYI `get_last_checkpoint` function from `trainer_utils` can be used to do exactly the same.

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## Your contribution

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I can raise a PR if it is a useful feature to have!
Instead of adding a new argument, I would use the existing `resume_from_checkpoint` and change its type to bool or str/PathLike. If it's a bool and if it's `True`, we then use `get_last_checkpoint` to get the last checkpoint in `args.output_dir`. Does that sound good to you?<|||||>Yes, SGTM. I have raised [a PR](https://github.com/huggingface/transformers/pull/10334) doing the same. Do let me know if there is any other change required as well!

**PS**: Can you also review my [other PR](https://github.com/huggingface/transformers/pull/10286) introducing `save_strategy` in `TrainingArguments`? This PR is the last one to round-up the `save_strategy`, `evaluation_strategy` and `logging_strategy` enhancements.  

Thanks!<|||||>> # 🚀 Feature request
> `Trainer.train` accepts `resume_from_checkpoint` argument, which requires the user to explicitly provide the checkpoint location to continue training from. `resume_from_last_checkpoint` can be useful to resume training by picking the latest checkpoint from `output_dir` of the `TrainingArguments` passed.
> 
> ## Motivation
> 1. The checkpoint directory is created by the library, so user needs to navigate to the directory to find the value to provide for `resume_from_checkpoint`
> 2. User may just want to resume from the last valid checkpoint since their training got disrupted previously (a common scenario for someone to want to resume training). All they know is the `output_dir` they provided initially
> 
> This motivates to provide a `resume_from_last_checkpoint=True` to the `Trainer.train(...)` call, which will pick the latest checkpoint from `args.output_dir`. FYI `get_last_checkpoint` function from `trainer_utils` can be used to do exactly the same.
> 
> ## Your contribution
> I can raise a PR if it is a useful feature to have!
Is it possible to train while adding a new category to the dataset using this resume_from_checkpoint argument?
