Scandeval

Fixed
- Now removing all empty documents from datasets, as well as catching
`KeyError` when trying to remove empty documents from dataset.

Fixed
- Now explicitly removing empty tokenisations from the dataset.

Fixed
- Now catching _all_ `CUDA error` exceptions and treating them as running out
of memory. No harm done if this is not the case, however, as the script will
simply decrease the batch size until it reaches 1, and if CUDA errors persist
then it will skip that benchmark.

Fixed
- When benchmarking a token classification dataset with a model whose tokenizer
does not have a fast variant yet, this raised an error as the `word_ids`
method of `BatchEncoding` objects only works when the tokenizer is fast. In
that case these word IDs are now computed manually. This can currently handle
WordPiece and SentencePiece prefixes (i.e., `` and `▁`), and will raise an
error if the manual alignment of words and tokens fail.
- Catch the CUDA error `CUDA error: CUBLAS_STATUS_ALLOC_FAILED`, which in this
case is due to OOM.

Fixed
- Deal with CUDA OOM errors when they occur on a replica, when multiple cores
are used.

Fixed
- Remove reference to `trainer` when CUDA OOM error is dealt with.