Datasets.map causes incorrect overflow_to_sample_mapping when used with tokenizers and small batch size
## Describe the bug
When using `tokenizer`, we can retrieve the field `overflow_to_sample_mapping`, since long samples will be overflown into multiple token sequences.

However, when tokenizing is done via `Dataset.map`, with `n_proc > 1`, the `overflow_to_sample_mapping` field is wrong.  This seems to be because each tokenizer only looks at its share of the samples, and maps to the index _within its share_, but then `Dataset.map` collates them together.

## Steps to reproduce the bug

1. Make a dataset of 3 strings.
2. Tokenize via Dataset.map with n_proc = 8
3. Inspect the `overflow_to_sample_mapping` field


## Expected results
`[0, 1, 2]`

## Actual results
`[0, 0, 0]`

Notes:

1. I have not yet extracted a minimal example, but the above works reliably
2. If the dataset is large, I've yet to determine if this bug still happens a. not at all b. always c. on the small, leftover batch at the end.
