Add self training code for text classification
This is an implementation of the self-training algorithm (without task augmentation) for classification tasks proposed in the [EMNLP 2021](https://2021.emnlp.org/) paper: [STraTA: Self-Training with Task Augmentation for Better Few-shot Learning](https://arxiv.org/abs/2109.06270).  For the original codebase, please check out https://github.com/google-research/google-research/tree/master/STraTA. Note that this code can be used as a tool for automatic data labeling.

The pull request includes a README.md file with detailed instructions on how to set up a virtual environment and install necessary packages. It also includes a demo `run.sh` on how to perform self-training with a BERT Base model on the SciTail science entailment dataset using 8 labeled examples per class.
_The documentation is not available anymore as the PR was closed or merged._<|||||>> Very nice, thanks a lot for adding this new example! Just to be sure, the empty strata file is intended? I didn't get why it's there.

Good catch, @sgugger. Just removed the empty strata file. Thanks!